Journal articles on the topic 'Heuristic research'
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Hyatt, Robert P. "Heuristic Research." Tradition and Discovery: The Polanyi Society Periodical 38, no. 3 (2011): 71–74. http://dx.doi.org/10.5840/traddisc2011/201238329.
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Liang, Rui Shi, and Min Huang. "Heuristics for Domain-Independent Planning: A Survey." Applied Mechanics and Materials 135-136 (October 2011): 573–77. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.573.
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Increasing interest has been devoted to Planning as Heuristic Search over the years. Intense research has focused on deriving fast and accurate heuristics for domain-independent planning. This paper reports on an extensive survey and analysis of research work related to heuristic derivation techniques for state space search. Survey results reveal that heuristic techniques have been extensively applied in many efficient planners and result in impressive performances. We extend the survey analysis to suggest promising avenues for future research in heuristic derivation and heuristic search techniques.
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Savolainen, Reijo. "Heuristics elements of information-seeking strategies and tactics: a conceptual analysis." Journal of Documentation 73, no. 6 (October 9, 2017): 1322–42. http://dx.doi.org/10.1108/jd-11-2016-0144.
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Purpose The purpose of this paper is to elaborate the picture of strategies and tactics for information seeking and searching by focusing on the heuristic elements of such strategies and tactics. Design/methodology/approach A conceptual analysis of a sample of 31 pertinent investigations was conducted to find out how researchers have approached heuristics in the above context since the 1970s. To achieve this, the study draws on the ideas produced within the research programmes on Heuristics and Biases, and Fast and Frugal Heuristics. Findings Researchers have approached the heuristic elements in three major ways. First, these elements are defined as general level constituents of browsing strategies in particular. Second, heuristics are approached as search tips. Third, there are examples of conceptualizations of individual heuristics. Familiarity heuristic suggests that people tend to prefer sources that have worked well in similar situations in the past. Recognition heuristic draws on an all-or-none distinction of the information objects, based on cues such as information scent. Finally, representativeness heuristic is based on recalling similar instances of events or objects and judging their typicality in terms of genres, for example. Research limitations/implications As the study focuses on three heuristics only, the findings cannot be generalized to describe the use of all heuristic elements of strategies and tactics for information seeking and searching. Originality/value The study pioneers by providing an in-depth analysis of the ways in which the heuristic elements are conceptualized in the context of information seeking and searching. The findings contribute to the elaboration of the conceptual issues of information behavior research.
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Wilt, Christopher, and Wheeler Ruml. "Effective Heuristics for Suboptimal Best-First Search." Journal of Artificial Intelligence Research 57 (October 31, 2016): 273–306. http://dx.doi.org/10.1613/jair.5036.
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Suboptimal heuristic search algorithms such as weighted A* and greedy best-first search are widely used to solve problems for which guaranteed optimal solutions are too expensive to obtain. These algorithms crucially rely on a heuristic function to guide their search. However, most research on building heuristics addresses optimal solving. In this paper, we illustrate how established wisdom for constructing heuristics for optimal search can fail when considering suboptimal search. We consider the behavior of greedy best-first search in detail and we test several hypotheses for predicting when a heuristic will be effective for it. Our results suggest that a predictive characteristic is a heuristic's goal distance rank correlation (GDRC), a robust measure of whether it orders nodes according to distance to a goal. We demonstrate that GDRC can be used to automatically construct abstraction-based heuristics for greedy best-first search that are more effective than those built by methods oriented toward optimal search. These results reinforce the point that suboptimal search deserves sustained attention and specialized methods of its own.
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Shanklin, Roslyn, Philip Kortum, and Claudia Ziegler Acemyan. "Adaptation of Heuristic Evaluations for the Physical Environment." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (December 2020): 1135–39. http://dx.doi.org/10.1177/1071181320641272.
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Previous work has investigated the need for domain specific heuristics. Nielsen’s ten heuristics offer a general list of principles, but those principles may not capture usability issues specific to a given interface. Studies have demonstrated methods to establish a domain specific heuristic set, but very little research has been conducted on interfaces in the physical environment, creating a gap in the state-of-the-art. The research described in this paper aims to address this gap by developing an environmental heuristic set; the heuristic set was developed specifically for the Houston light rail system, METRORail. Following development, the heuristic set was validated against Nielsen’s more general heuristics through several field studies. Results highlighted that there were significantly more usability issues identified when using the environment-based heuristics than the general heuristics. This suggests that domain specific heuristics provide a framework that allows evaluators to capture usability issues particular to the interface of the physical environment.
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Ursani, Ziauddin, and David W. Corne. "Introducing Complexity Curtailing Techniques for the Tour Construction Heuristics for the Travelling Salesperson Problem." Journal of Optimization 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/4786268.
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In this paper, complexity curtailing techniques are introduced to create faster version of insertion heuristics, that is, cheapest insertion heuristic (CIH) and largest insertion heuristic (LIH), effectively reducing their complexities fromO(n3)toO(n2)with no significant effect on quality of solution. This paper also examines relatively not very known heuristic concept of max difference and shows that it can be culminated into a full-fledged max difference insertion heuristic (MDIH) by defining its missing steps. Further to this the paper extends the complexity curtailing techniques to MDIH to create its faster version. The resultant heuristic, that is, fast max difference insertion heuristic (FMDIH), outperforms the “farthest insertion” heuristic (FIH) across a wide spectrum of popular datasets with statistical significance, even though both the heuristics have the same worst case complexity ofO(n2). It should be noted that FIH is considered best among lowest order complexity heuristics. The complexity curtailing techniques presented here open up the new area of research for their possible extension to other heuristics.
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Özcan, Ender, Mustafa Misir, Gabriela Ochoa, and Edmund K. Burke. "A Reinforcement Learning - Great-Deluge Hyper-Heuristic for Examination Timetabling." International Journal of Applied Metaheuristic Computing 1, no. 1 (January 2010): 39–59. http://dx.doi.org/10.4018/jamc.2010102603.
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Hyper-heuristics can be identified as methodologies that search the space generated by a finite set of low level heuristics for solving search problems. An iterative hyper-heuristic framework can be thought of as requiring a single candidate solution and multiple perturbation low level heuristics. An initially generated complete solution goes through two successive processes (heuristic selection and move acceptance) until a set of termination criteria is satisfied. A motivating goal of hyper-heuristic research is to create automated techniques that are applicable to a wide range of problems with different characteristics. Some previous studies show that different combinations of heuristic selection and move acceptance as hyper-heuristic components might yield different performances. This study investigates whether learning heuristic selection can improve the performance of a great deluge based hyper-heuristic using an examination timetabling problem as a case study.
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Drake, John H., Matthew Hyde, Khaled Ibrahim, and Ender Ozcan. "A genetic programming hyper-heuristic for the multidimensional knapsack problem." Kybernetes 43, no. 9/10 (November 3, 2014): 1500–1511. http://dx.doi.org/10.1108/k-09-2013-0201.
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Purpose – Hyper-heuristics are a class of high-level search techniques which operate on a search space of heuristics rather than directly on a search space of solutions. The purpose of this paper is to investigate the suitability of using genetic programming as a hyper-heuristic methodology to generate constructive heuristics to solve the multidimensional 0-1 knapsack problem Design/methodology/approach – Early hyper-heuristics focused on selecting and applying a low-level heuristic at each stage of a search. Recent trends in hyper-heuristic research have led to a number of approaches being developed to automatically generate new heuristics from a set of heuristic components. A population of heuristics to rank knapsack items are trained on a subset of test problems and then applied to unseen instances. Findings – The results over a set of standard benchmarks show that genetic programming can be used to generate constructive heuristics which yield human-competitive results. Originality/value – In this work the authors show that genetic programming is suitable as a method to generate reusable constructive heuristics for the multidimensional 0-1 knapsack problem. This is classified as a hyper-heuristic approach as it operates on a search space of heuristics rather than a search space of solutions. To our knowledge, this is the first time in the literature a GP hyper-heuristic has been used to solve the multidimensional 0-1 knapsack problem. The results suggest that using GP to evolve ranking mechanisms merits further future research effort.
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HIGGINS, A. J. "A PERCENTILE SEARCH HEURISTIC FOR GENERALIZED ASSIGNMENT PROBLEMS WITH A VERY LARGE NUMBER OF JOBS." Asia-Pacific Journal of Operational Research 22, no. 02 (June 2005): 171–88. http://dx.doi.org/10.1142/s0217595905000492.
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This article presents a new heuristic for generalized assignment problems with a very large number of jobs. The heuristic applies a probabilistic acceptance of a move, based on a percentile threshold, using information from recent moves. This percentile search heuristic (PSH) is compared to tabu search, simulated annealing, and threshold accepting using a rigorous computational experimentation with randomly generated problem instances of up to 50,000 jobs and 40 agents. The PSH did find the best solution among the heuristics for 45% of the instances, particularly larger size problems, versus 30% for tabu search, but required more fine-tuning of the heuristic parameters.
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Goldenberg, Meir. "The Heuristic Search Research Framework." Knowledge-Based Systems 129 (August 2017): 1–3. http://dx.doi.org/10.1016/j.knosys.2017.05.009.
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Pham, V. H., M. Martinez, and J. Favrel. "Assembly Sequence Generation - Heuristic Research." IFAC Proceedings Volumes 31, no. 31 (November 1998): 139–44. http://dx.doi.org/10.1016/s1474-6670(17)41018-4.
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Fortunato, David, and Randolph T. Stevenson. "Heuristics in Context." Political Science Research and Methods 7, no. 2 (October 17, 2016): 311–30. http://dx.doi.org/10.1017/psrm.2016.37.
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A growing literature in political science has pointed to the importance of heuristics in explaining citizens’ political attitudes, beliefs, and behaviors. At the same time, the multidisciplinary research on heuristics in general has revealed that individuals seem to use heuristics sensibly—applying them (perhaps subconsciously) when they are likely to be helpful but not otherwise. We extend this multidisciplinary work to political behavior and present a general theory of contextual variation in political heuristic use applied to discover under what conditions (i.e., what political contexts) voters will use a partisanship heuristic to infer the legislative votes of their legislators in imperfectly disciplined voting contexts. More specifically, we predict that US constituents of loyal partisan senators will use the partisanship heuristic more often than constituents of less loyal senators. Our empirical analysis reveals strong support for our theory, contributing to our understanding of political heuristics in general and adding nuance to our understanding of the partisanship heuristic in particular.
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Ericson, Keith Marzilli, and Amanda Starc. "Heuristics and Heterogeneity in Health Insurance Exchanges: Evidence from the Massachusetts Connector." American Economic Review 102, no. 3 (May 1, 2012): 493–97. http://dx.doi.org/10.1257/aer.102.3.493.
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We examine heuristic decision rules in consumer choice on health insurance exchanges using data from the Massachusetts Connector. Consumers may have difficulty making optimal choices in a complex environment. The heuristic “choose the cheapest plan” is suggested by the decision context, previous research, and the data: about 20% of enrollees choose the cheapest plan possible. We find evidence of this heuristic in many models, but while heuristics may play a role, preference heterogeneity is also important. Our most flexible models find an insignificant heuristic effect. In part because holding context fixed, this heuristic is observationally equivalent to extreme price sensitivity.
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Rott, Benjamin. "Rethinking heuristics – characterizations and vignettes." Lumat: International Journal of Math, Science and Technology Education 3, no. 1 (February 28, 2015): 122–26. http://dx.doi.org/10.31129/lumat.v3i1.1055.
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The concept of “heuristics” or “heuristic strategies” is central to (mathematical) problem solving and related research; however, there is no generally accepted definition of this term. Trying to clarify the concept might help avoiding misunderstandings and difficulties in dealing with studies that use different terms meaning the same concepts or that use the same terms meaning different concepts. Therefore, the research presented in this paper aims at a clarification of the term “heuristics” and suggestions for the use of it in future research. Building on previous work from last year’s ProMath conference, the consequences of using different characterizations of “heuristics” on vignettes (= short, completed scenes) of problem solving attempts are investigated. The conceptualization of “heuristics” has a significant influence on the types and numbers of perceived heuristics, which in turn affects empirical studies that identify and analyze heuristic strategies.
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Štukelj, Gašper. "On the simplicity of simple heuristics." Adaptive Behavior 28, no. 4 (August 6, 2019): 261–71. http://dx.doi.org/10.1177/1059712319861589.
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Recent evidence suggests that the take-the-best heuristic—flagship of “fast and frugal heuristics” research program—might in fact not be as frugal as tallying, which is considered to be a more complex strategy. Characterizing a simple decision strategy has always seemed straightforward, and the debate around the simplicity of the take-the-best heuristic is mostly concerned with a proper specification of the heuristic. I argue that the predominate conceptions of “simplicity” and “frugality” need to be revised. To this end, a number of recent behavioral and neuroscientific results are discussed. The example of take-the-best heuristic serves as an entry point to a foundational debate on bounded agency. I argue that the fast and frugal heuristics needs to question some of its legacy from the classical AI research. For example, the assumption that the bottleneck of decision-making process is information processing due to its serial nature. These commitments are hard to reconcile with the modern neuroscientific view of a human decision-maker. In addition, I discuss an overlooked source of uncertainty, namely neural noise, and compare a generic heuristic model to a similar neural algorithm.
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Lohmüller, Valentin, Daniel Schmaderer, and Christian Wolff. "A Heuristic Checklist for Second Screen Applications." i-com 18, no. 1 (April 26, 2019): 55–65. http://dx.doi.org/10.1515/icom-2019-0003.
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Abstract This paper presents domain-specific heuristics for second screen applications and the development of a heuristics checklist to enable a more intuitive and structured application of the created heuristics. The heuristics presented were developed on the basis of Nielsen [12] Ten Usability Heuristics in a research-based approach using specific literature and a focus group. In order to evaluate the quality of the derived checklist, a heuristic evaluation of a second screen application with five users was carried out and its results compared to a user study with 20 participants. This resulted in an average validity of 0.5 and a high completeness of 0.74. The harmonic mean of these values results in an F-measure of 0.6 with an equal weighting. This value speaks for a sufficient validity of the created heuristic checklist in the first iteration.
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Jasper, Fabian, and Tuulia M. Ortner. "The Tendency to Fall for Distracting Information While Making Judgments." European Journal of Psychological Assessment 30, no. 3 (January 1, 2014): 193–207. http://dx.doi.org/10.1027/1015-5759/a000214.
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Despite much research on thinking biases such as the representativeness, availability, and anchoring heuristics, a psychometrically sound measurement instrument for assessing the degree of heuristic thinking is still missing. Therefore, it was the goal of this study to develop and validate a new test to assess the degree of heuristic thinking associated with three particular thinking heuristics (i.e., the representativeness, availability, and anchoring heuristics). The resulting Objective Heuristic Thinking Test (OHTT) was evaluated with regard to its internal consistency, factor structure, construct validity, and stability in an internet sample (N = 300) and an independent laboratory sample (N = 55). Exploratory factor analyses resulted in three latent factors that represented the three OHTT subscales (i.e., representativeness, availability, and anchoring factors). Results revealed a low to sufficient internal consistency for each of the three scales. Further analyses indicated convergent correlations of the OHTT scales with related constructs such as field-independency. Furthermore, good stability of the test scores was shown. Conclusions are drawn regarding possible future applications of the OHTT as a promising tool for studying the origins of heuristic thinking processes.
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Shevlin, Henry. "General Intelligence: An Ecumenical Heuristic for Artificial Consciousness Research?" Journal of Artificial Intelligence and Consciousness 07, no. 02 (July 27, 2020): 245–56. http://dx.doi.org/10.1142/s2705078520500149.
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The science of consciousness has made great strides in recent decades. However, the proliferation of competing theories makes it difficult to reach consensus about artificial consciousness. While for purely scientific purposes we might wish to adopt a ‘wait and see’ attitude, we may soon face practical and ethical questions about whether, for example, agents artificial systems are capable of suffering. Moreover, many of the methods used for assessing consciousness in humans and even non-human animals are not straightforwardly applicable to artificial systems. With these challenges in mind, I propose that we look for ecumenical heuristics for artificial consciousness to enable us to make tentative assessments of the likelihood of consciousness arising in different artificial systems. I argue that such heuristics should have three main features: they should be (i) intuitively plausible, (ii) theoretically-neutral, and (iii) scientifically tractable. I claim that the concept of general intelligence — understood as a capacity for robust, flexible, and integrated cognition and behavior — satisfies these criteria and may thus provide the basis for such a heuristic, allowing us to make initial cautious estimations of which artificial systems are most likely to be conscious.
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Weis, Patrick P., and Eva Wiese. "Speed Considerations Can Be of Little Concern When Outsourcing Thought to External Devices." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (September 2018): 14–18. http://dx.doi.org/10.1177/1541931218621004.
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Most research on human cognition has focused on processes “inside the box”. Recently, researchers questioned this monopoly, promoting the relevance of cognitive processing “outside the box”, for instance, when using a GPS to navigate. For processing that is distributed between internal and external resources to work efficiently, humans need good heuristics that help them decide when to use which resource. A novel human-computer-interaction paradigm was employed to explore whether people follow the “minimal memory” heuristic and offload cognitive processing onto external resources whenever possible or the “soft constraint” heuristic and offload cognitive processing only if it is associated with an overall higher speed than internal processing. Participants, despite lower speed, nearly exclusively cognized outside the box, which contradicts the soft constraint heuristic and mostly supports the minimal memory heuristic. Implications for human-technology interaction as well as alternative heuristics relevant for cognitive offloading are discussed.
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West, Todd, John Sessions, and Bogdan M. Strimbu. "Heuristic Optimization of Thinning Individual Douglas-Fir." Forests 12, no. 3 (February 28, 2021): 280. http://dx.doi.org/10.3390/f12030280.
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Research Highlights: (1) Optimizing mid-rotation thinning increased modeled land expectation values by as much as 5.1–10.1% over a representative reference prescription on plots planted at 2.7 and 3.7 m square spacings. (2) Eight heuristics, five of which were newly applied to selecting individual trees for thinning, produced thinning prescriptions of near identical quality. (3) Based on heuristic sampling properties, we introduced a variant of the hero heuristic with a 5.3–20% greater computational efficiency. Background and Objectives: Thinning, which is arguably the most subjective human intervention in the life of a stand, is commonly executed with limited decision support in tree selection. This study evaluated heuristics’ ability to support tree selection in a factorial experiment that considered the thinning method, tree density, thinning age, and rotation length. Materials and Methods: The Organon growth model was used for the financial optimization of even age Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) harvest rotations consisting of a single thinning followed by clearcutting on a high-productivity site. We evaluated two versions of the hero heuristic, four Monte Carlo heuristics (simulated annealing, record-to-record travel, threshold accepting, and great deluge), a genetic algorithm, and tabu search for their efficiency in maximizing land expectation value. Results: With 50–75 years rotations and a 4% discount rate, heuristic tree selection always increased land expectation values over other thinning methods. The two hero heuristics were the most computationally efficient methods. The four Monte Carlo heuristics required 2.8–3.4 times more computation than hero. The genetic algorithm and the tabu search required 4.2–8.4 and 21–52 times, respectively, more computation than hero. Conclusions: The accuracy of the resulting thinning prescriptions was limited by the quality of stand measurement, and the accuracy of the growth and yield models was linked to the heuristics rather than to the choice of heuristic. However, heuristic performance may be sensitive to the chosen models.
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Ríos-Mercado, Roger Z. "Special issue of the Journal of Heuristics on “Heuristic Research: Advances and Applications”." Journal of Heuristics 15, no. 2 (June 20, 2008): 105–7. http://dx.doi.org/10.1007/s10732-008-9086-y.
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Cavarretta, Fabrice L. "On the hard problem of selecting bundles of rules: a conceptual exploration of heuristic emergence processes." Management Decision 59, no. 7 (May 10, 2021): 1598–616. http://dx.doi.org/10.1108/md-09-2019-1322.
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PurposeSo far, the simplicity of heuristics has been mostly studied at the rule level. However, actors' bounded rationality implies that small bundles of rules drive behavior. This study thus conducts a conceptual elaboration around such bundling. This leads to reflections on the various processes of heuristic emergence and to qualifications of the respective characteristics of basic heuristic classes.Design/methodology/approachDetermining which rules – out of many possible ones – to select in one's small bundle constitutes a difficult combinatorial problem. Fortunately, past research has demonstrated that solutions can be found in evolutionary mechanisms. Those converge toward bundles that are somewhat imperfect yet cannot be easily improved, a.k.a., locally optimal bundles. This paper therefore identifies that heuristic bundles can efficiently emerge by social evolutionary mechanisms whereby actors recursively exchange, adopt and perform bundles of rules constitute processes of heuristic emergence.FindingsSuch evolutionary emergence of socially calculated small bundles of heuristics differs from the agentic process by which some simple rule heuristics emerge or from the biological calculation process by which some behavioral biology heuristics emerge. The paper subsequently proceeds by classifying heuristics depending on their emergence process, distinguishing, on the one hand, agentic vs evolutionary mechanisms and, on the other hand, social vs biological encodings. The differences in the emergence processes of heuristics suggest the possibility of comparing them on three key characteristics – timescale, reflectivity and local optimality – which imply different forms of fitness.Research limitations/implicationsThe study proceeds as a conceptual elaboration; hence, it does not provide empirics. At a microlevel, it enables classification and comparison of the largest possible range of heuristics. At a macrolevel, it advocates for further exploration of managerial bundles of rules, regarding both their dynamics and their substantive nature.Practical implicationsIn the field, practitioners are often observed to socially construct their theory of action, which emerges as a bundle of heuristics. This study demonstrates that such social calculations provide solutions that have comparatively good qualities as compared to heuristics emerging through other processes, such as agentic simple rules or instinctive – i.e. behavioral biology – heuristics. It should motivate further research on bundles of heuristics in management practice. Such an effort would improve the ability to produce knowledge fitting the absorptive capacity of practitioners and enhance the construction of normative managerial theories and pedagogy.Social implicationsBundles of rules may also play a crucial role in the emergence of collective action. This study contributes to a performativity perspective whereby theories can become reality. It demonstrates how the construction of a managerial belief system may amount to the launching of a social movement and vice versa.Originality/valueOverall, many benefits accrue from integrating the bundles of rules expressed and exchanged by practitioners under the heuristic umbrella. So far, in management scholarship, such emergent objects have sometimes been interpreted as naïve or as indicative of institutional pressures. By contrast, this study shows that socially calculated bundles may efficiently combine the advantages of individuals' reflective cognitive processes with those provided by massive evolutionary exchanges. In conclusion, the social calculations of small heuristic bundles may constitute a crucial mechanism for the elaboration of pragmatic theories of action.
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Hanafi, Saïd, Jasmina Lazic, Nenad Mladenovic, Christophe Wilbaut, and Igor Crévits. "New variable neighbourhood search based 0-1 MIP heuristics." Yugoslav Journal of Operations Research 25, no. 3 (2015): 343–60. http://dx.doi.org/10.2298/yjor140219014h.
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In recent years many so-called matheuristics have been proposed for solving Mixed Integer Programming (MIP) problems. Though most of them are very efficient, they do not all theoretically converge to an optimal solution. In this paper we suggest two matheuristics, based on the variable neighbourhood decomposition search (VNDS), and we prove their convergence. Our approach is computationally competitive with the current state-of-the-art heuristics, and on a standard benchmark of 59 0-1 MIP instances, our best heuristic achieves similar solution quality to that of a recently published VNDS heuristic for 0-1 MIPs within a shorter execution time.
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Knappertsbusch, Felix. "“Fractal Heuristics” for Mixed Methods Research: Applying Abbott’s “Fractal Distinctions” as a Conceptual Metaphor for Method Integration." Journal of Mixed Methods Research 14, no. 4 (December 19, 2019): 456–72. http://dx.doi.org/10.1177/1558689819893573.
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With the interest in advancing integration in the field of mixed methods research (MMR), researchers need powerful metaphors for conceiving and implementing mixing strategies. This article contributes to the field of MMR by showing how Abbott’s “fractal distinctions” provide a valuable heuristic for the application of method combinations as well as the methodological reflection of MMR. Based on its core notion, the “self-similarity” of methods approaches, I propose three heuristic guidelines: (a) deliberately seek out qualitative aspects in quantitative methods (and vice versa); (b) assume a nonessentialist, theory-oriented approach toward method integration; and (c) aim to reconcile rigor and innovation in empirical research. I discuss similarities between fractal heuristics and other conceptualizations of difference-within, including dialectical and feminist approaches to MMR.
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Burke, Edmund K., Matthew R. Hyde, Graham Kendall, and John Woodward. "Automating the Packing Heuristic Design Process with Genetic Programming." Evolutionary Computation 20, no. 1 (March 2012): 63–89. http://dx.doi.org/10.1162/evco_a_00044.
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The literature shows that one-, two-, and three-dimensional bin packing and knapsack packing are difficult problems in operational research. Many techniques, including exact, heuristic, and metaheuristic approaches, have been investigated to solve these problems and it is often not clear which method to use when presented with a new instance. This paper presents an approach which is motivated by the goal of building computer systems which can design heuristic methods. The overall aim is to explore the possibilities for automating the heuristic design process. We present a genetic programming system to automatically generate a good quality heuristic for each instance. It is not necessary to change the methodology depending on the problem type (one-, two-, or three-dimensional knapsack and bin packing problems), and it therefore has a level of generality unmatched by other systems in the literature. We carry out an extensive suite of experiments and compare with the best human designed heuristics in the literature. Note that our heuristic design methodology uses the same parameters for all the experiments. The contribution of this paper is to present a more general packing methodology than those currently available, and to show that, by using this methodology, it is possible for a computer system to design heuristics which are competitive with the human designed heuristics from the literature. This represents the first packing algorithm in the literature able to claim human competitive results in such a wide variety of packing domains.
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VALENTE, JORGE M. S. "BEAM SEARCH HEURISTICS FOR THE SINGLE MACHINE SCHEDULING PROBLEM WITH LINEAR EARLINESS AND QUADRATIC TARDINESS COSTS." Asia-Pacific Journal of Operational Research 26, no. 03 (June 2009): 319–39. http://dx.doi.org/10.1142/s0217595909002225.
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In this paper, we consider the single machine scheduling problem with linear earliness and quadratic tardiness costs, and no machine idle time. We present heuristic algorithms based on the beam search technique. These algorithms include classic beam search procedures, as well as the filtered and recovering variants. Several dispatching rules are considered as evaluation functions, to analyze the effect of different rules on the effectiveness of the beam search algorithms. The computational results show that using better rules improves the performance of the beam search heuristics. The detailed, filtered beam search (FBS) and recovering beam search (RBS) procedures outperform the best existing heuristic. The best results are given by the recovering and detailed variants, which provide objective function values that are quite close to the optimum. For small to medium size instances, either of these procedures can be used. For larger instances, the detailed beam search (DBS) algorithm requires excessive computation times, and the RBS procedure then becomes the heuristic of choice.
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Van Allen, Eliezer Mendel, Nikhil Wagle, Gregory Kryukov, Alexis Ramos, Gad Getz, and Levi A. Garraway. "A heuristic platform for clinical interpretation of cancer genome sequencing data." Journal of Clinical Oncology 30, no. 15_suppl (May 20, 2012): 10502. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.10502.
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10502 Background: The ability to identify and effectively sort the full spectrum of biologically and therapeutically relevant genetic alterations identified by massively parallel sequencing may improve cancer care. A major challenge involves rapid and rational categorization of data-intensive output, including somatic mutations, insertions/deletions, copy number alterations, and rearrangements into ranked categories for clinician review. Methods: A database of clinically actionable alterations was created, consisting of over 100 annotated genes known to undergo somatic genomic alterations in cancer that may impact clinical decision-making. A heuristic algorithm was developed, which selectively identifies somatic alterations based on the clinically actionable alterations database. Remaining variants are sorted based on additional heuristics, including high priority alterations based on presence in the Cancer Gene Census, biologically significant cancer genes based on presence in COSMIC or MSigDB, and low priority alterations in the same gene family as biologically significant cancer genes. The heuristic algorithm was applied to whole exome sequencing data of clinical samples and whole genome sequencing data from a cohort of prostate cancer samples processed using established Broad Institute pipelines. Results: Application of the heuristic algorithm to the prostate cancer whole genome rearrangement data identified 172 (out of 5978) rearrangements involving actionable genes (averaging 2-3 events per tumor). Furthermore, two clinical samples processed prospectively were analyzed, yielding three potentially actionable alterations for clinical review. Conclusions: The heuristic model for clinical interpretation of next generation sequencing data may facilitate rapid analysis of tumor genomic information for clinician review by identifying and prioritizing alterations that can directly impact care. Our platform can also be applied to research data to prospectively explore clinically relevant findings from existing cohorts. Future analytical approaches using heuristic or probabilistic algorithms should underpin a robust prospective assessment of clinical cancer genome data.
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Alquhayz, Hani, and Mahdi Jemmali. "Max-Min Processors Scheduling." Information Technology and Control 50, no. 1 (March 25, 2021): 5–12. http://dx.doi.org/10.5755/j01.itc.50.1.25531.
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This paper focuses on the maximization of the minimum completion time on identical parallel processors. The objective of this maximization is to ensure fair distribution. Let a set of jobs to be assigned to several identical parallel processors. This problem is shown as NP-hard. The research work of this paper is based essentially on the comparison of the proposed heuristics with others cited in the literature review. Our heuristics are developed using essentially the randomization method and the iterative utilization of the knapsack problem to solve the studied problem. Heuristics are assessed by several instances represented in the experimental results. The results show that the knapsack based heuristic gives almost a similar performance than heuristic in a literature review but in better running time.
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Han, Ai Li. "Complexity Research on B Algorithm." Applied Mechanics and Materials 20-23 (January 2010): 173–77. http://dx.doi.org/10.4028/www.scientific.net/amm.20-23.173.
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The time complexity of B algorithm, one of the intelligent search algorithms, is discussed. By anatomizing some instances, it is pointed out that the cost of calculating the value of heuristic function should be included in the range of time complexity analysis for B algorithm. And then, an algorithm of calculating the value of heuristic function is presented. By analyzing the cost of calculating the value of heuristic function, it is pointed out that the number of recursions in B algorithm is O(n!) in the worst case. Therefore, the time complexity of B algorithm is exponential instead of O(n2).
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Tarraq, Ali, Faissal Elmariami, Aziz Belfqih, and Touria Haidi. "Meta-heuristic optimization methods applied to renewable distributed generation planning: A review." E3S Web of Conferences 234 (2021): 00086. http://dx.doi.org/10.1051/e3sconf/202123400086.
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Due to its proven efficiency and computational speed, the most recent developed meta-heuristic optimization methods are widely used to better integrate renewable distributed generation (RDG) into the electricity grid. The main objective of this paper is to obtain a better knowledge of current trends in meta-heuristics applied to optimally integrate RDGs to the distribution network. This is a review of well known meta-heuristic approaches, used to solve the problem of optimal renewable distributed generation allocation planning (ORDGAP). In this context, some research gaps were mentioned, and recommendations were proposed to expand the scope of research in this field.
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McKay, David A., and Oscar Mink. "Validity in organizational research: A heuristic model." Human Resource Development Quarterly 3, no. 1 (1992): 51–71. http://dx.doi.org/10.1002/hrdq.3920030106.
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Gonzaga de Oliveira, Sanderson L., and Libério M. Silva. "Low-cost heuristics for matrix bandwidth reduction combined with a Hill-Climbing strategy." RAIRO - Operations Research 55, no. 4 (July 2021): 2247–64. http://dx.doi.org/10.1051/ro/2021102.
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This paper studies heuristics for the bandwidth reduction of large-scale matrices in serial computations. Bandwidth optimization is a demanding subject for a large number of scientific and engineering applications. A heuristic for bandwidth reduction labels the rows and columns of a given sparse matrix. The algorithm arranges entries with a nonzero coefficient as close to the main diagonal as possible. This paper modifies an ant colony hyper-heuristic approach to generate expert-level heuristics for bandwidth reduction combined with a Hill-Climbing strategy when applied to matrices arising from specific application areas. Specifically, this paper uses low-cost state-of-the-art heuristics for bandwidth reduction in tandem with a Hill-Climbing procedure. The results yielded on a wide-ranging set of standard benchmark matrices showed that the proposed strategy outperformed low-cost state-of-the-art heuristics for bandwidth reduction when applied to matrices with symmetric sparsity patterns.
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Pugazhenthi, R., and M. Anthony Xavior. "Minimizing Material Processing Time and Idle Time of a Critical Machine in a Flow Shop." Advanced Materials Research 984-985 (July 2014): 106–10. http://dx.doi.org/10.4028/www.scientific.net/amr.984-985.106.
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In this research article aims to develop a heuristic for minimizing the total material processing time and idle time of the critical machine in a flow shop. This heuristic is proposed through the Exponential Distribution (ED) factor which helps in developing a mathematical model with less computational instance. When the idle time of the critical machine is reduced then it is indirectly affects the total material processing time of the flow shop, which makes the objective of critical machine utilization as vital. And a set of constrain had been established to position the critical machines in the flow shop. For several instance, computational experiments had done using the benchmark problems, among other heuristics ED heuristic yields a better result.
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Moser, Andrea K. "Buying organic – decision-making heuristics and empirical evidence from Germany." Journal of Consumer Marketing 33, no. 7 (November 14, 2016): 552–61. http://dx.doi.org/10.1108/jcm-04-2016-1790.
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Purpose Identifying the drivers that positively influence consumption of organic products is of utmost importance to reach consumers beyond the niche. Therefore, this study aims to propose an innovative framework which conceptualizes motivating beliefs and a simple decision-making heuristic as predictors of buying organic. Design/methodology/approach A structural equation approach is applied. Data were obtained from a nationwide panel (n = 1,760) and included survey data and scanner data for five different food categories. Findings The model is supported by actual purchasing data in all categories. While beliefs explained about 75 per cent of the variance in the decision-making heuristic for organic products, the heuristic in turn predicted up to 20 per cent of the variance in buying behavior. Research limitations/implications Further research should aim to validate the proposed constructs and relationships and refine the factors. Practical implications Consumers have to understand and value the benefits of organic products. Self-interested and environmental beliefs are equally strong motivations which can be seen as an opportunity for marketing. Originality/value The results contribute to understanding the structure and the impact of heuristics and quantify the competing beliefs by which heuristics are driven.
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Li, Yingping, Wei Wang, Hui Cai, Jian Chen, and Ying Wang. "The Research of Home Energy Management Strategy Based on a New Meta-Heuristic Algorithm." International Journal of Materials, Mechanics and Manufacturing 6, no. 6 (December 2018): 407–14. http://dx.doi.org/10.18178/ijmmm.2018.6.6.417.
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Tian, Li, Qiang Qiang Wang, and An Zhao Cao. "Research on SVM Line Loss Rate Prediction Based on Heuristic Algorithm." Applied Mechanics and Materials 291-294 (February 2013): 2164–68. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2164.
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With the characteristic of line loss volatility, a research of line loss rate prediction was imperatively carried out. Considering the optimization ability of heuristic algorithm and the regression ability of support vector machine, a heuristic algorithm-support vector machine model is constructed. Case study shows that, compared with other heuristic algorithms’, the search efficiency and speed of genetic algorithm are good, and the prediction model is with high accuracy.
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Chen, James C., Chien Wei Wu, Tran Dinh Duy Thao, Ling Huey Su, Wen Haiung Hsieh, and Tiffany Chen. "Hybrid Genetic Algorithm for Solving Assembly Line Balancing Problem in Footwear Industry." Advanced Materials Research 939 (May 2014): 623–29. http://dx.doi.org/10.4028/www.scientific.net/amr.939.623.
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This research develops a heuristic algorithm for assembly line balancing problem (ALBP) of stitching lines in footwear industry. The proposed algorithm can help to design the stitching line with workstations, machines and operators for the production of every new product model. Rank-positional-weighted heuristics and hybrid genetic algorithms are proposed to solve ALBP. First, the heuristics assign tasks and machines to workstations. This solution is then used as an initiative population for hybrid genetic algorithm for further improvement. Real data from footwear manufacturers and experimental designs are used to verify the performance of the proposed algorithm, comparing with one existing bidirectional heuristic. Results indicate that when the size and shape of shoes increase, the proposed genetic algorithm achieves better solution quality than existing heuristics.Production managers can use the research results to quickly design stitching lines for short production cycle time and high labor utilization.
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Sihotang, Emil Hasudungan, Muhamad Adam, Marlina Widiyanti, and Yuliani Yuliani. "PENGARUH PERILAKU KEUANGAN HEURISTIK TERHADAP KEPUTUSAN INVESTASI SAHAM PADA BURSA EFEK INDONESIA DENGAN INVESTASI ETIS SEBAGAI VARIABEL INTERVENING STUDI EMPIRIS PADA MASYARAKAT INVESTOR KOTA PALEMBANG." Jurnal Riset Ekonomi dan Bisnis 13, no. 1 (April 21, 2020): 28. http://dx.doi.org/10.26623/jreb.v13i1.2108.
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<p class="BasicParagraph">Tujuan dari penelitian ini untuk mengetahui bukti empiris pengaruh perilaku keuangan heuristik (<em>salience, rerpresentativness dan mental accounting</em>) dan investasi etis terhadap keputusan investasi saham yang dilakukan oleh investor individu di kota Palembang pada tahun 2019. Penelitian ini bersifat kausal menggunakan data primer 145 responden dengan teknik purposive sampling. Program analisis Structural Equation Modeling (SEM) Amos digunakan untuk mengukur hubungan antara variabel penelitian. Hasil penelitian menunjukkan bahwa perilaku keuangan heuristik salience dan mental accounting berpengaruh signifikan terhadap keputusan investasi, sedangkan <em>representativness</em> tidak signifikan terhadap keputusan investasi dan investasi etis mampu memediasi perilaku keuangan heuristik terhadap keputusan investasi.</p><p class="BasicParagraph"><strong><em>The purpose of this study is to find out empirical evidence of the influence of financial heuristics (salience, rerpresentativness and mental accounting) and ethical investment on investment decisions made by individual investors in the city of Palembang in 2019. This study uses causal data using primary data of 145 respondents with taking techniques purposive sample. Analysis of the Amos Structural Equation Modeling (SEM) program is used to measure the relationship between research variables. The results showed heuristic financial facts salience and mental accounting have a significant effect on investment decisions, while representation does not have a significant effect on investment returns and ethical investment is able to mediate heuristic financial problems on investment decisions.</em></strong></p>
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Xu, Yan-xin. "An Efficient Heuristic Approach for Irregular Cutting Stock Problem in Ship Building Industry." Mathematical Problems in Engineering 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/8703782.
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This paper presents an efficient approach for solving a real two-dimensional irregular cutting stock problem in ship building industry. Cutting stock problem is a common cutting and packing problem that arises in a variety of industrial applications. A modification of selection heuristic Exact Fit is applied in our research. In the case referring to irregular shapes, a placement heuristics is more important to construct a complete solution. A placement heuristic relating to bottom-left-fill is presented. We evaluate the proposed approach using generated instance only with convex shapes in literatures and some instances with nonconvex shapes based on real problem from ship building industry. The results demonstrate that the effectiveness and efficiency of the proposed approach are significantly better than some conventional heuristics.
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Bornstein, Claudio Thomas, and Manoel Campêlo. "An ADD/DROP procedure for the capacitated plant location problem." Pesquisa Operacional 24, no. 1 (April 2004): 151–62. http://dx.doi.org/10.1590/s0101-74382004000100008.
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The capacitated plant location problem with linear transportation costs is considered. Exact rules and heuristics are presented for opening or closing of facilities. A heuristic algorithm based on ADD/DROP strategies is proposed. Procedures are implemented with the help of lower and upper bounds using Lagrangean relaxation. Computational results are presented and comparisons with other algorithms are made.
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Urosevic, Dragan. "Variable neighborhood search for maximum diverse grouping problem." Yugoslav Journal of Operations Research 24, no. 1 (2014): 21–33. http://dx.doi.org/10.2298/yjor121223003u.
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This paper presents a general variable neighborhood search (GVNS) heuristic for solving the maximum diverse grouping problem. Extensive computational experiments performed on a series of large random graphs as well as on several instances of the maximum diversity problem taken from the literature show that the results obtained by GVNS consistently outperform the best heuristics from the literature.
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Vis, Barbara. "Heuristics and Political Elites’ Judgment and Decision-Making." Political Studies Review 17, no. 1 (February 1, 2018): 41–52. http://dx.doi.org/10.1177/1478929917750311.
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It is broadly assumed that political elites (e.g. party leaders) regularly rely on heuristics in their judgments or decision-making. In this article, I aim to bring together and discuss the scattered literature on this topic. To address the current conceptual unclarity, I discuss two traditions on heuristics: (1) the heuristics and biases (H&B) tradition pioneered by Kahneman and Tversky and (2) the fast and frugal heuristics (F&F) tradition pioneered by Gigerenzer et al. I propose to concentrate on two well-defined heuristics from the H&B tradition— availability and representativeness—to empirically assess when political elites rely on heuristics and thereby understand better their judgments and decisions. My review of existing studies supports the notion that political elites use the availability heuristic and possibly the representativeness one for making complex decisions under uncertainty. It also reveals that besides this, we still know relatively little about when political elites use which heuristic and with what effect(s). Therefore, I end by proposing an agenda for future research.
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Vilchynskaya, Liudmila. "DEVELOPMENT OF INTERNAL MOTIVATION OF EDUCATIONAL ACTIVITY IN STUDENTS-ATHLETES ON THE BASIS OF USE OF HEURISTIC METHODS IN TEACHING SUBJECT "ANATOMY"." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 1 (May 26, 2017): 422. http://dx.doi.org/10.17770/sie2017vol1.2302.
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In the article the role of heuristic methods of training in development of an intrinsic motivation of the educational activity of students of specialty "Physical culture" reveals. The methodological basis of research is constituted by pedagogical heuristics – methodology of training through own search. Content of heuristic training includes two parts: invariant which is set from the outside and is acquired by the student, and variable, created by each of them in the course of educational activity.The problem of research is formulated as a question: how it is possible to strengthen an intrinsic motivation of educational activities of students during teaching subject "Anatomy".The orientation of motivation of studying by students of subject "Anatomy" came to light by T. D. Dubovitskaya's test (reliability 0,935 (on Spirmen-Brown's formula) and 0,927 (on Cronbach's formula)). The data on change of dynamics of the academic progress of students confirming efficiency of heuristic methods are also provided in article.
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Rötheli, Tobias. "Heuristics versus econometrics as a basis for forecasting international inflation differentials." foresight 21, no. 2 (April 8, 2019): 216–26. http://dx.doi.org/10.1108/fs-07-2018-0070.
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Purpose This study aims to address the issue of prediction of inflation differences for an economy that considers either fixing its exchange rate or joining a currency union. In this setting, individual countries have limited control over their inflation, and anticipating the possible course of domestic inflation relative to inflation abroad becomes an important input in policy-making. In this context, the author compares simple forecast heuristics and econometric modeling. Design/methodology/approach The study compares two basically different approaches. The first approach of forecasting consists of simple heuristics. Various heuristics are considered that differ with respect to the economic reasoning that goes into quantifying the forecast rules. The simplest such forecasting heuristic suggests that the average over all available observations of inflation differentials should be taken as a predictor for the future. Bringing more economic insight to bear suggests a further heuristic according to which historical inflation differentials should be adjusted for changes in the nominal exchange rate. A further variant of this approach suggests that a forecast should exclusively rely on data from earlier times under a pegged exchange rate. A fundamentally different approach to prediction builds on dynamic econometric models estimated by using all available historical data independent of the currency regime. Findings The author studies three small member countries of the Eurozone, i.e. Finland, Luxembourg and Portugal. For the evaluation of the various forecasting strategies, he performs out-of-sample predictions over a horizon of five years. The comparison of the four different forecasting strategies documents that the variant of the forecast heuristic that draws on data from earlier experiences under fixed exchange rates performs better than the forecast based on the estimated econometric model. Practical implications The findings of this study provide helpful guidelines for countries considering either joining a currency union or fixing their exchange rate. The author shows that a simple forecasting heuristic gives sound advice for assessing the likely course of inflation. Originality/value This study describes how economic theory can guide the selection of historical data for assessing likely future developments. The analysis shows that using a simple heuristic based on historical analogy can lead to better forecasts than the analytically more sophisticated approach of econometric modeling.
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Peng, Ya Li, Jia Yao Liu, and Hong Yin. "Research on Vehicle Path Planning Based on the BDD in the Uncertain Environment." Applied Mechanics and Materials 373-375 (August 2013): 1144–49. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.1144.
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Aimed at the high dynamics and uncertainty of road traffic, we propose a method combine BDD (binary decision diagram)-Based heuristic algorithm which used to do the initial path planning with BDD-Based incremental to solve the route replanning problem. In order to get the optimal path set, BDD-Based heuristic Search is firstly used for global planning. BDD is a compact data structure, the BDD-Based heuristic Search use this characteristic to represent state space and compress the search space through heuristic information at the same time; when the road network information changes, incremental replanning was used in difference type of congestion and the optimum path set again. The simulation results show that the BDD-Based heuristic Search and incremental replanning method has high efficiency and practicability in solving vehicle routing problem under dynamic and uncertain environment.
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Aickelin, Uwe, and Alistair Clark. "Heuristic optimisation." Journal of the Operational Research Society 62, no. 2 (February 2011): 251–52. http://dx.doi.org/10.1057/jors.2010.160.
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Chen, James C., Wun Hao Jaong, Cheng Ju Sun, Hung Yu Lee, Jenn Sheng Wu, and Chung Chao Ku. "Applying Genetic Algorithm to Resource Constrained Multi-Project Scheduling Problems." Key Engineering Materials 419-420 (October 2009): 633–36. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.633.
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Resource-constrained multi-project scheduling problems (RCMPSP) consider precedence relationship among activities and the capacity constraints of multiple resources for multiple projects. RCMPSP are NP-hard due to these practical constraints indicating an exponential calculation time to reach optimal solution. In order to improve the speed and the performance of problem solving, heuristic approaches are widely applied to solve RCMPSP. This research proposes Hybrid Genetic Algorithm (HGA) and heuristic approach to solve RCMPSP with an objective to minimize the total tardiness. HGA is compared with three typical heuristics for RCMPSP: Maximum Total Work Content, Earliest Due Date, and Minimum Slack. Two typical RCMPSP from literature are used as a test bed for performance evaluation. The results demonstrate that HGA outperforms the three heuristic methods in term of the total tardiness.
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Shah, Syed Zulfiqar Ali, Maqsood Ahmad, and Faisal Mahmood. "Heuristic biases in investment decision-making and perceived market efficiency." Qualitative Research in Financial Markets 10, no. 1 (February 5, 2018): 85–110. http://dx.doi.org/10.1108/qrfm-04-2017-0033.
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Purpose This paper aims to clarify the mechanism by which heuristics influences the investment decisions of individual investors, actively trading on the Pakistan Stock Exchange (PSX), and the perceived efficiency of the market. Most studies focus on well-developed financial markets and very little is known about investors’ behaviour in less developed financial markets or emerging markets. The present study contributes to filling this gap in the literature. Design/methodology/approach Investors’ heuristic biases have been measured using a questionnaire, containing numerous items, including indicators of speculators, investment decisions and perceived market efficiency variables. The sample consists of 143 investors trading on the PSX. A convenient, purposively sampling technique was used for data collection. To examine the relationship between heuristic biases, investment decisions and perceived market efficiency, hypotheses were tested by using correlation and regression analysis. Findings The paper provides empirical insights into the relationship of heuristic biases, investment decisions and perceived market efficiency. The results suggest that heuristic biases (overconfidence, representativeness, availability and anchoring) have a markedly negative impact on investment decisions made by individual investors actively trading on the PSX and on perceived market efficiency. Research limitations/implications The primary limitation of the empirical review is the tiny size of the sample. A larger sample would have given more trustworthy results and could have empowered a more extensive scope of investigation. Practical implications The paper encourages investors to avoid relying on heuristics or their feelings when making investments. It provides awareness and understanding of heuristic biases in investment management, which could be very useful for decision makers and professionals in financial institutions, such as portfolio managers and traders in commercial banks, investment banks and mutual funds. This paper helps investors to select better investment tools and avoid repeating expensive errors, which occur due to heuristic biases. They can improve their performance by recognizing their biases and errors of judgment, to which we are all prone, resulting in a more efficient market. So, it is necessary to focus on a specific investment strategy to control “mental mistakes” by investors, due to heuristic biases. Originality/value The current study is the first of its kind, focusing on the link between heuristics, individual investment decisions and perceived market efficiency within the specific context of Pakistan.
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Xu, Qiang, Le-chang Sun, and Hai-tao Liu. "Research on the Heuristic Bootstrapping Mechanism for Kademlia." Journal of Electronics & Information Technology 33, no. 2 (March 3, 2011): 266–71. http://dx.doi.org/10.3724/sp.j.1146.2010.00348.
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Gregory, Robert Wayne, and Jan Muntermann. "Research Note—Heuristic Theorizing: Proactively Generating Design Theories." Information Systems Research 25, no. 3 (September 2014): 639–53. http://dx.doi.org/10.1287/isre.2014.0533.
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