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Journal articles on the topic 'Heuristic processes'

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Author: Grafiati

Published: 31 August 2024

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1

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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Cao, Qianning. "The Availability Heuristic." Communications in Humanities Research 27, no. 1 (March 1, 2024): 271–74. http://dx.doi.org/10.54254/2753-7064/27/20231715.

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Few fields of psychology have undergone such dramatic conceptual changes over the past dozen years as the emerging science of heuristics. Heuristics are effective cognitive processes that consciously or unconsciously ignore part of information. Good heuristics can greatly reduce the time it takes to solve a problem by avoiding some unlikely possibilities, and although heuristic processes tend to find solutions or outcomes that are often valid or correct, they may only be correct, provable, optimal, or accurate sometimes. However, decision making based on heuristics is often sufficient to solve small-scale problems and provide solutions in uncertain situations where complete information is not available. Heuristics rely on shortcuts to provide immediate, efficient and short-term solutions to facilitate timely decision making. People need to understand how cognitive heuristics work in an uncertain world, combined with practical applications or theory, to help analyze the performance and use areas of heuristics, so that they can continue to evolve and improve.

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3

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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Gragson, Ted L. "Heuristic Mapping of Frontier Processes." Field Methods 14, no. 4 (November 2002): 368–89. http://dx.doi.org/10.1177/152582202237726.

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5

Grodzinsky, Yosef, and Alexander Marek. "Algorithmic and heuristic processes revisited." Brain and Language 33, no. 2 (March 1988): 216–25. http://dx.doi.org/10.1016/0093-934x(88)90065-x.

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6

Du, Ruibo. "Availability Heuristic: An Overview and Applications." Highlights in Business, Economics and Management 1 (November 28, 2022): 153–59. http://dx.doi.org/10.54097/hbem.v1i.2548.

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Heuristics exist in all individuals, causing irrational and often false conclusions on the frequency and probability of events. With the recognition of behavioral finance theories, this essay includes an overview, applications, and analysis of a particular heuristic, the availability heuristic. It focuses on the potential misjudgment that may result from the availability heuristic, in order to provide an alternative perspective for economic and social issues. This essay may build a better understanding of the availability heuristic for market participants and policymakers; reducing the degree and frequency of misjudgment and human errors in influential decision-making processes.

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Wimsatt, William C. "Heuristics refound." Behavioral and Brain Sciences 23, no. 5 (October 2000): 766–67. http://dx.doi.org/10.1017/s0140525x00513442.

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Gigerenzer et al.'s is an extremely important book. The ecological validity of the key heuristics is strengthened by their relation to ubiquitous Poisson processes. The recognition heuristic is also used in conspecific cueing processes in ecology. Three additional classes of problem-solving heuristics are proposed for further study: families based on near-decomposability analysis, exaptive construction of functional structures, and robustness.

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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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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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Karakoyun, Gülen Önal, and Erol Asiltürk. "Analysis of Pre-Service Science Teachers’ Heuristic Reasoning Processes about Hydrogen Bonding." Journal of Science Learning 4, no. 1 (November 27, 2020): 50–60. http://dx.doi.org/10.17509/jsl.v4i1.23737.

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The purpose of this research was to determine the heuristics used by pre-service science teachers in understanding the details of hydrogen bonding. The reasoning processes demonstrated were evaluated based on ten heuristic models suggested by Talanquer (2014). Phenomenographic assessment of the 30 participants indicated that all ten heuristics were utilized to make interpretations about hydrogen bonding. It was found that most students used short-cut strategies rather than efficient analytical reasoning processes. A total of 12 answer patterns were determined based on the answers of the participants. The percentage of students who gave the correct answer was low. The frequency sequencing of participants' heuristics demonstrated in this study was fluency, associative activation, recognition, one-reason decision making, attribute substitution, overconfidence, surface similarity, generalization, rigidity, and affect.

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Luyben, William L. "Heuristic Design of Reaction/Separation Processes." Industrial & Engineering Chemistry Research 49, no. 22 (November 17, 2010): 11564–71. http://dx.doi.org/10.1021/ie101509w.

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12

Rosburg, Timm, Axel Mecklinger, and Christian Frings. "When the Brain Decides." Psychological Science 22, no. 12 (November 3, 2011): 1527–34. http://dx.doi.org/10.1177/0956797611417454.

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Humans can make fast and highly efficient decisions by using simple heuristics that are assumed to exploit basic cognitive functions. In the study reported here, we used event-related potentials (ERPs) to disclose the psychological mechanisms underlying one of the most frugal decision rules, namely, the recognition heuristic. According to this heuristic, whenever two objects have to be ranked by a specific criterion and only one object is recognized, the recognized object is ranked higher than the unrecognized object. Using a standard recognition-heuristic paradigm, we predicted participants’ decisions by analyzing an ERP correlate of familiarity-based recognition occurring 300 to 450 ms after stimulus onset. The measure remained a significant predictor even when later ERP correlates were taken into account. These findings are evidence for the thesis that simple heuristics exploit basic cognitive processes. Specifically, the findings show that familiarity—that is, recognition in the absence of recollection—contributes to decisions made on the basis of such heuristics.

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Davies, Simon P. "Memory and Planning Processes in Solutions to Well-Structured Problems." Quarterly Journal of Experimental Psychology Section A 53, no. 3 (August 2000): 896–927. http://dx.doi.org/10.1080/713755909.

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Although many studies in the problem-solving literature have considered the factors that might determine the strategies that are employed to solve well-structured problems, these have typically focused upon variants of means-end analysis. In general, such models imply that strategies unfold in a temporally forward direction, that problem solvers typically restrict forward-planning activities to just one or two moves ahead of the current problem state, and that one important heuristic is the avoidance of previous moves. Although studies have demonstrated the importance of such anti-looping heuristics, few have systematically explored the possibility that problem solvers may also plan retrospectively in order to try and assess whether a move might take them back to a state that they have previously visited. Those models of problem solving that promote the role of an anti-looping heuristic have assumed that the ability to use such a heuristic is based upon memory for previous states, but other interpretations are possible. In this paper several studies are reported that attempt systematically to explore participants’ attempts to recognize previously visited problem solving states. The findings suggest that there is a systematic relationship between the success of this process, the time taken to make this judgement, and distance from the current state. It is also demonstrated that estimations about where future positions are likely to occur are symmetrical to estimations about past positions. It is suggested that this provides evidence that problem solvers engage in retrospective planning processes in order to try and avoid previous moves, and that this strategy may not be based straightforwardly upon their ability to remember previous problem states.

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Spanos, P. D., W. Y. Tein, and R. G. Ghanem. "Heuristic spectral estimation of bivariate nonstationary processes." Meccanica 31, no. 2 (April 1996): 207–18. http://dx.doi.org/10.1007/bf00426261.

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Fernández, Joaquín L., Rafael Sanz, Reid G. Simmons, and Amador R. Diéguez. "Heuristic anytime approaches to stochastic decision processes." Journal of Heuristics 12, no. 3 (May 2006): 181–209. http://dx.doi.org/10.1007/s10732-006-4834-3.

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Gárate-Escamilla, Anna Karen, Ivan Amaya, Jorge M. Cruz-Duarte, Hugo Terashima-Marín, and José Carlos Ortiz-Bayliss. "Identifying Hyper-Heuristic Trends through a Text Mining Approach on the Current Literature." Applied Sciences 12, no. 20 (October 20, 2022): 10576. http://dx.doi.org/10.3390/app122010576.

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Hyper-heuristics have arisen as methods that increase the generality of existing solvers. They have proven helpful for dealing with complex problems, particularly those related to combinatorial optimization. Their recent growth in popularity has increased the daily amount of text in the related literature. This information is primarily unstructured, mainly text that traditional computer data systems cannot process. Traditional systematic literature review studies exhibit multiple limitations, including high time consumption, lack of replicability, and subjectivity of the results. For this reason, text mining has become essential for researchers in recent years. Therefore, efficient text mining techniques are needed to extract meaningful information, patterns, and relationships. This study adopts a literature review of 963 journal and conference papers on hyper-heuristic-related works. We first describe the essential text mining techniques, including text preprocessing, word clouds, clustering, and frequent association rule learning in hyper-heuristic publications. With that information, we implement visualization tools to understand the most frequent relations and topics in the hyper-heuristic domain. The main findings highlight the most dominant topics in the literature. We use text mining analysis to find widespread manifestations, representing the significance of the different areas of hyper-heuristics. Furthermore, we apply clustering to provide seven categories showing the associations between the topics related to hyper-heuristic literature. The vast amount of data available that we find opens up a new opportunity for researchers to analyze the status of hyper-heuristics and help create strategic plans regarding the scope of hyper-heuristics. Lastly, we remark that future work will address the limitations of collecting information from multiple data sources and analyze book chapters related to hyper-heuristics.

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Sánchez-Díaz, Xavier, José Carlos Ortiz-Bayliss, Ivan Amaya, Jorge M. Cruz-Duarte, Santiago Enrique Conant-Pablos, and Hugo Terashima-Marín. "A Feature-Independent Hyper-Heuristic Approach for Solving the Knapsack Problem." Applied Sciences 11, no. 21 (October 31, 2021): 10209. http://dx.doi.org/10.3390/app112110209.

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Recent years have witnessed a growing interest in automatic learning mechanisms and applications. The concept of hyper-heuristics, algorithms that either select among existing algorithms or generate new ones, holds high relevance in this matter. Current research suggests that, under certain circumstances, hyper-heuristics outperform single heuristics when evaluated in isolation. When hyper-heuristics are selected among existing algorithms, they map problem states into suitable solvers. Unfortunately, identifying the features that accurately describe the problem state—and thus allow for a proper mapping—requires plenty of domain-specific knowledge, which is not always available. This work proposes a simple yet effective hyper-heuristic model that does not rely on problem features to produce such a mapping. The model defines a fixed sequence of heuristics that improves the solving process of knapsack problems. This research comprises an analysis of feature-independent hyper-heuristic performance under different learning conditions and different problem sets.

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Wu, Zhiying, Qingxin Chen, Ning Mao, and Guoning Xu. "Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand." Applied Sciences 13, no. 18 (September 6, 2023): 10070. http://dx.doi.org/10.3390/app131810070.

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In this paper, we propose a deterministic shift design model with task-based demand and give the corresponding stochastic version with a probability constraint such that the shift plan designed is staffed with the workforce with a certain probability of performing all given tasks. Since we currently find no suitable methods for solving this stochastic model from the literature related to solving stochastic shift design models, we developed a single-stage heuristic method based on statistics, whose main idea is to reduce the occurrence of manpower shortage by prolonging the resource occupation time of a task, but this leads to a serious waste of resources, which is common in solving resource allocation problems with uncertain durations. To reduce the cost of wastage, we also propose a two-stage heuristic approach that is a two-stage heuristic with an evolutionary strategy. The two heuristics show their effectiveness in solving the proposed stochastic model in numerical experiments, and the two-stage heuristic significantly outperforms the one-stage heuristic in cost optimization and solution time stability.

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Nadurak, Vitaliy. "Moral Heuristics and Two Types of Information Processing." Acta Baltica Historiae et Philosophiae Scientiarum 10, no. 2 (December 11, 2022): 46–62. http://dx.doi.org/10.11590/abhps.2022.2.03.

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The purpose of this paper is to clarify the relationship between moral heuristics and two types of information processing. To achieve this goal, moral heuristics will be considered in the context of a dual-process theory. Type 1 processes (deliberate) are being defined as consciously controlled and Type 2 processes (intuitive) as those that occur without conscious control. Heuristics are not one of the types of information processing, but a methodor procedure that simplifies information processing for decision-makers. This simplification can be achieved both in deliberate and intuitive ways. Therefore, heuristics can operate at the different levels of the information processing. The level at which heuristics work depends on the heuristic itself, the person (their experience, cognitive qualities, etc.), environment, and problem that needs to be solved.

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Shchekhovska, Larysa. "Behavioral implications in supply chain risk management." Electronic Scientific Journal Intellectualization of Logistics and Supply Chain Management #1 2020, no. 21 (October 2023): 22–32. http://dx.doi.org/10.46783/smart-scm/2023-21-3.

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This article provides new insights into behavioral implications based on biases and heuristics in SCRM. It is argued that biases and heuristics will play an even greater role in SCRM as the rising complexity of risk management systems has increasingly overstrained the cognitive abilities of decision-makers. The main contribution and central finding of the article is the presentation of a wide array of behavioral implications of the selected biases and heuristics for SCRM. It is differentiated between four major SCRM processes: risk identification, risk assessment, risk treatment, and risk monitoring. Focusing on each process individually allows for a dedicated and in-depth presentation of the behavioral implications in SCRM. It is stated that risk identification, where biases and heuristics such as confirmation bias and the availability heuristics can lead to a skewed identification of risks, resulting in omitted risks or the selection of irrelevant risks. In risk assessment, the behavioral implications can be equally severe with the consequence of incorrectly assessing the impact and probability of risks as caused for example through the availability heuristic or representative heuristic. The risk treatment is equally prone to biases and heuristics, as for example loss aversion or planning fallacy can lead to over- or underinvesting in risk treatments as well as wrong estimates about the required costs and effort. The risk monitoring is impacted through biases and heuristics such as the anchoring and adjustment heuristic or the confirmation bias, due to which risk managers carry out insufficient or unnecessary adjustments regarding their risk management system.

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Saksuriya, Payakorn, and Chulin Likasiri. "Hybrid Heuristic for Vehicle Routing Problem with Time Windows and Compatibility Constraints in Home Healthcare System." Applied Sciences 12, no. 13 (June 26, 2022): 6486. http://dx.doi.org/10.3390/app12136486.

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This work involves a heuristic for solving vehicle routing problems with time windows (VRPTW) with general compatibility-matching between customer/patient and server/caretaker constraints to capture the nature of systems such as caretakers’ home visiting systems or home healthcare (HHC) systems. Since any variation of VRPTW is more complicated than regular VRP, a specific, custom-made heuristic is needed to solve the problem. The heuristic proposed in this work is an efficient hybrid of a novice Local Search (LS), Ruin and Recreate procedure (R&R) and Particle Swarm Optimization (PSO). The proposed LS acts as the initial solution finder as well as the engine for finding a feasible/local optimum. While PSO helps in moving from current best solution to the next best solution, the R&R part allows the solution to be over-optimized and LS moves the solution back on the feasible side. To test our heuristic, we solved 56 benchmark instances of 25, 50, and 100 customers and found that our heuristics can find 52, 21, and 18 optimal cases, respectively. To further investigate the proficiency of our heuristic, we modified the benchmark instances to include compatibility constraints. The results show that our heuristic can reach the optimal solutions in 5 out of 56 instances.

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AlFayez, Fayez. "Architecture and enhanced-algorithms to manage servers-processes into network: a management system." PeerJ Computer Science 9 (July 18, 2023): e1408. http://dx.doi.org/10.7717/peerj-cs.1408.

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This work investigates minimizing the makespan of multiple servers in the case of identical parallel processors. In the case of executing multiple tasks through several servers and each server has a fixed number of processors. The processors are generally composed of two processors (core duo) or four processors (quad). The meaningful format of the number of processors is 2k, and k ≥ 0. The problem is to find a schedule that minimizes the makespan on 2k processors. This problem is identified as NP-hard one. A new network architecture is proposed based on the addition of server management. In addition, two novel algorithms are proposed to solve the addressed scheduling problems. The proposed algorithms are based on the decomposition of the main problem in several sub-problems that are applied to develop new heuristics. In each level of the generated tree, some results are saved and used to decompose the set of processes into subsets for the next level. The proposed methods are experimentally examined showing that the running time of the proposed heuristics is remarkably better than its best rival from the literature. The application of this method is devoted to the network case when there are several servers to be exploited. The experimental results show that in 87.9% of total instances, the most loaded and least loaded subset-sum heuristic (MLS) reaches the best solution. The best-proposed heuristic reaches in 87.4% of cases the optimal solution in an average time of 0.002 s compared with the best of the literature which reaches a solution in an average time of 1.307 s.

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White, D. J. "An Heuristic for Multi-Dimensional Markov Decision Processes." Journal of Information and Optimization Sciences 14, no. 2 (May 1993): 203–19. http://dx.doi.org/10.1080/02522667.1993.10699150.

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Andersson, Linus, Johan Eriksson, Sara Stillesjö, Peter Juslin, Lars Nyberg, and Linnea Karlsson Wirebring. "Neurocognitive processes underlying heuristic and normative probability judgments." Cognition 196 (March 2020): 104153. http://dx.doi.org/10.1016/j.cognition.2019.104153.

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Buitrago, Manuel, José M. Adam, Yezid A. Alvarado, Juan J. Moragues, Isabel Gasch, and Pedro A. Calderón. "Designing construction processes in buildings by heuristic optimization." Engineering Structures 111 (March 2016): 1–10. http://dx.doi.org/10.1016/j.engstruct.2015.12.009.

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Expósito-Izquierdo, Christopher, Belén Melián-Batista, and José Marcos Moreno-Vega. "Optimization Model and Heuristic Approach for Blocks Retrieval Processes in Warehouses." Proceedings of the International Conference on Automated Planning and Scheduling 24 (May 10, 2014): 111–19. http://dx.doi.org/10.1609/icaps.v24i1.13634.

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In this paper we introduce a planning problem termed as Q-Blocks Relocation Problem, which pursues to retrieve a subset of blocks located in a warehouse by minimizing the number of relocation movements. We formalize the problem by means of a Mixed Integer Linear Programming model. However, the high computational burden required by the model encourages us to develop a heuristic algorithm for tackling it. The rationale behind the proposed heuristic is both to retrieve the requested blocks as soon as possible while reducing the number of blocks placed above another one with a higher priority. The computational results indicate that the heuristic reports near-optimal solutions for realistic instances by short computational times, which makes it attractive to be applied by management systems.

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hahn, ulrike, john-mark frost, and greg maio. "what's in a heuristic?" Behavioral and Brain Sciences 28, no. 4 (August 2005): 551–52. http://dx.doi.org/10.1017/s0140525x05320097.

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the term “moral heuristic” as used by sunstein seeks to bring together various traditions. however, there are significant differences between uses of the term “heuristic” in the cognitive and the social psychological research, and these differences are accompanied by very distinct evidential criteria. we suggest the term “moral heuristic” should refer to processes, which means that further evidence is required.

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Klimenko, I. S. "Heuristic methods of decision support in project management." Sovremennaya nauka i innovatsii, no. 4 (44) (2023): 10–19. http://dx.doi.org/10.37493/2307-910x.2023.4.1.

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The article is devoted to the use of informal methods in the processes of justification of choice and decision-making in project activities. The classification of selection methods is given, the essence of project activity is determined, its fundamental difference from operational activity. The significance and value of heuristic practices for increasing the validity of a design decision is shown.

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Ahn, Hyun-Soo, and Rhonda Righter. "Multi-Actor Markov Decision Processes." Journal of Applied Probability 42, no. 1 (March 2005): 15–26. http://dx.doi.org/10.1239/jap/1110381367.

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We give a very general reformulation of multi-actor Markov decision processes and show that there is a tendency for the actors to take the same action whenever possible. This considerably reduces the complexity of the problem, either facilitating numerical computation of the optimal policy or providing a basis for a heuristic.

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Ahn, Hyun-Soo, and Rhonda Righter. "Multi-Actor Markov Decision Processes." Journal of Applied Probability 42, no. 01 (March 2005): 15–26. http://dx.doi.org/10.1017/s0021900200000024.

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We give a very general reformulation of multi-actor Markov decision processes and show that there is a tendency for the actors to take the same action whenever possible. This considerably reduces the complexity of the problem, either facilitating numerical computation of the optimal policy or providing a basis for a heuristic.

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Pazis, Jason, and Ronald Parr. "PAC Optimal Exploration in Continuous Space Markov Decision Processes." Proceedings of the AAAI Conference on Artificial Intelligence 27, no. 1 (June 30, 2013): 774–81. http://dx.doi.org/10.1609/aaai.v27i1.8678.

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Current exploration algorithms can be classified in two broad categories: Heuristic, and PAC optimal. While numerous researchers have used heuristic approaches such as epsilon-greedy exploration successfully, such approaches lack formal, finite sample guarantees and may need a significant amount of fine-tuning to produce good results. PAC optimal exploration algorithms, on the other hand, offer strong theoretical guarantees but are inapplicable in domains of realistic size. The goal of this paper is to bridge the gap between theory and practice, by introducing C-PACE, an algorithm which offers strong theoretical guarantees and can be applied to interesting, continuous space problems.

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Lewis, Timothy B., and Jeffrey N. Barnes. "An Accounting Liability Heuristic." Journal of Business Case Studies (JBCS) 11, no. 4 (October 5, 2015): 189–224. http://dx.doi.org/10.19030/jbcs.v11i4.9447.

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This article traces the thought processes involved in understanding and managing accountants’ legal liability which is sometimes broadly called “professional malpractice.” The cumulative nature of potential liability is demonstrated. The various legal theories of liability are discussed along with the most prominent potential affirmative defenses against liability. Unique to this paper is the decision heuristic providing a framework for assessing potential accountants’ legal liability. This discussion is useful for both student and practitioner.

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Mohagheghi, Mohammadsadegh, and Khayyam Salehi. "Improving Graph-based methods for computing qualitative properties of markov decision processes." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 3 (March 1, 2020): 1571. http://dx.doi.org/10.11591/ijeecs.v17.i3.pp1571-1577.

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<span>Probabilistic model checking is a formal verification method, which is used to guarantee the correctness of the computer systems with stochastic behaviors. Reachability probabilities are the main class of properties that are proposed in probabilistic model checking. Some graph-based pre-computation can determine those states for which the reachability probability is exactly zero or one. Iterative numerical methods are used to compute the reachability probabilities for the remaining states. In this paper, we focus on the graph-based pre-computations and propose a heuristic to improve the performance of these pre-computations. The proposed heuristic approximates the set of states that are computed in the standard pre-computation methods. The experiments show that the proposed heuristic can compute a main part of the expected states, while reduces the running time by several orders of magnitude.</span>

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34

Schroyens, Walter, Walter Schaeken, Wim Fias, and Géry d'Ydewalle. "Heuristic and analytic processes in propositional reasoning with negatives." Journal of Experimental Psychology: Learning, Memory, and Cognition 26, no. 6 (November 2000): 1713–34. http://dx.doi.org/10.1037/0278-7393.26.6.1713.

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Schembecker, G. "Heuristic-numeric design of separation processes for azeotropic mixtures." Computers & Chemical Engineering 21, no. 1-2 (1997): S231—S236. http://dx.doi.org/10.1016/s0098-1354(97)00054-9.

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Schembecker, Gerhard, and Karl Hans Simmrock. "Heuristic-numeric design of separation processes for azeotropic mixtures." Computers & Chemical Engineering 21 (May 1997): S231—S236. http://dx.doi.org/10.1016/s0098-1354(97)87507-2.

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Luyben, William L. "Heuristic Design of Reaction/Separation Processes with Two Recycles." Industrial & Engineering Chemistry Research 50, no. 8 (April 20, 2011): 4788–95. http://dx.doi.org/10.1021/ie101896v.

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David, J., P. Švec, R. Garzinová, S. Kluska-Nawarecka, D. Wilk-Kołodziejczyk, and K. Regulski. "Heuristic modeling of casting processes under the conditions uncertainty." Archives of Civil and Mechanical Engineering 16, no. 2 (February 2016): 179–85. http://dx.doi.org/10.1016/j.acme.2015.10.006.

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Su, Kexin. "The Introduction and Applications of Representativeness Heuristics." BCP Social Sciences & Humanities 19 (August 30, 2022): 645–50. http://dx.doi.org/10.54691/bcpssh.v19i.1804.

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Representativeness heuristic is one of the major cognitive shortcuts behaviours that instead a question of probability on one of similarity. Individuals are good at using representativeness method to solve problems since it is easier and faster to evaluate how closely the problem corresponds to a similar one. However, the customary use of representativeness heuristic may generate severe biases and errors by mental shortcuts, especially on judgements and probability estimations processes. Nowadays, the study of representativeness heuristic has practical significances and widely influences on residential daily activities and commercial operations from decision-making perspective. This paper will continue on analysing the representativeness heuristic further regarding to its fundamental theory, connotation, and applications on different fields to explain how representativeness heuristic to affect people’s decision-making processes and other behaviours imperceptibly through a qualitative research method. By means of analysing three cases in stock market, political behaviours, and medical diagnosis, this paper finds that it is possible to avoid the biases and errors caused by representativeness heuristic mental shortcuts through practicing systematically and increasing awareness effectively.

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Kaczmar, Ireneusz, and Tamás Bányai. "Optimisation of flow shop scheduling problem: simulation system vs. evolutive solver." Advanced Logistic Systems - Theory and Practice 16, no. 1 (July 8, 2022): 31–40. http://dx.doi.org/10.32971/als.2022.003.

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In the Industry 4.0 era the optimisation of production processes become more and more important. A wide range of tools are used to improve the performance of production processes and related operations of the supply chain including purchasing, distribution and inverse processes. These tools have a great impact on the results of design and operation of production processes both technology and logistics point of view. Within the frame of this article, the authors are demonstrating the optimisation potentials of simulation tools and heuristic solvers (optimisers) through the problem of the well-knows permutation flow shop scheduling. They are describing the models and methods used in the case of FlexSim simulation systems and the heuristic solver option of Excel Solver. As the numerical results show, both the simulation model and the heuristic optimisation approach lead to a quasi-optimal solution.

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Segovia-Aguas, Javier, Sergio Jiménez Celorrio, Laura Sebastiá, and Anders Jonsson. "Scaling-Up Generalized Planning as Heuristic Search with Landmarks." Proceedings of the International Symposium on Combinatorial Search 15, no. 1 (July 17, 2022): 171–79. http://dx.doi.org/10.1609/socs.v15i1.21765.

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Landmarks are one of the most effective search heuristics for classical planning, but largely ignored in generalized planning. Generalized planning (GP) is usually addressed as a combinatorial search in a given space of algorithmic solutions, where candidate solutions are evaluated w.r.t. the instances they solve. This type of solution evaluation ignores any sub-goal information that is not explicit in the representation of the planning instances, causing plateaus in the space of candidate generalized plans. Furthermore, node expansion in GP is a run-time bottleneck since it requires evaluating every child node over the entire batch of classical planning instances in a GP problem. In this paper we define a landmark counting heuristic for GP (that considers sub-goal information that is not explicitly represented in the planning instances), and a novel heuristic search algorithm for GP (that we call PGP) and that progressively processes subsets of the planning instances of a GP problem. Our two orthogonal contributions are analyzed in an ablation study, showing that both improve the state-of-the-art in GP as heuristic search, and that both benefit from each other when used in combination.

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Bonollo, Michele, Luca Di Persio, and Luca Prezioso. "The Default Risk Charge approach to regulatory risk measurement processes." Dependence Modeling 6, no. 1 (December 1, 2018): 309–30. http://dx.doi.org/10.1515/demo-2018-0018.

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AbstractIn the present paper we consider the Default Risk Charge (DRC) measure as an effective alternative to the Incremental Risk Charge (IRC) one, proposing its implementation by a quasi exhaustive-heuristic algorithm to determine the minimum capital requested to a bank facing the market risk associated to portfolios based on assets issued by several financial agents. While most of the banks use the Monte Carlo simulation approach and the empirical quantile to estimate this risk measure, we provide new computational approaches, exhaustive or heuristic, currently becoming feasible because of both the new regulation and to the high speed - low cost technology available nowadays. Concrete algorithms and numerical examples are provided to illustrate the effectiveness of the proposed techniques.

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Skakalina, E. "INTELLECTUAL CONTROL OF LOGISTIC PROCESSES USING GENETIC ALGORITHMS." Системи управління, навігації та зв’язку. Збірник наукових праць 1, no. 63 (February 26, 2021): 111–14. http://dx.doi.org/10.26906/sunz.2021.1.111.

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Global business digitalization entails the automation of a large number of business processes, both key and auxiliary. This trend is becoming a defining factor in the global BPM market. Intelligent systems for automating business processes cover not only the corporate segment of large corporate business, but quickly penetrate into medium-sized businesses and find application in government agencies. A strategic guideline in the digitalization of flow control is an innovative approach, which should be systematic. The proposed concept of digitalization of logistics processes is implemented on a heuristic basis, which corresponds to the permanence of the transition from traditional management of complex systems to logistics management and is determined by the degree of penetration of logistics management to all levels. The use of precise methods to optimize transportation cannot be implemented due to the difficulty of taking into account the external parameters and time constraints imposed by the dimension of the problem. The heuristic approach to which the genetic algorithm belongs is considered

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Mazurkiewicz, Małgorzata. "Heuristic methods as a powerful managerial tool for enterprise in times of uncertainty." Kwartalnik Nauk o Przedsiębiorstwie 63, no. 1 (March 31, 2022): 57–70. http://dx.doi.org/10.33119/knop.2022.63.1.5.

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In managing enterprise, uncertainty belongs to the attributes of the decision making processes. In competitive environments, where success depends on high-quality decisions, taking the wrong steps can lead to loss of market share or even contribute to running out of business. That is why it is important to choose from the many alternatives those methods which will be most effective in solving problems in a simple and quick way, and heuristics offer such a solution, which has proved its usefulness in uncertain business environments. The aim of this study is to present and evaluate heuristic methods and show their specificity and applicability in management science for enterprises in times of uncertainty. In this article, the theoretical aspect of managerial heuristics is presented, and the emphasis is also placed on presenting practical examples of applying heuristics in companies with times of uncertainty, but also in these times of the Covid-19 pandemic. The study also offers conclusions and provides practi al recommendations.

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Леонов, Юрий, Yuriy Leonov, Евгений Леонов, Evgeniy Leonov, Анастасия Зуева, Anastasiya Zueva, Анна Сазонова, and Anna Sazonova. "SEARCH OF OPTIMUM ENGINEERING PROCESSES USING ALGORITHMS OF HEURISTIC SEARCH." Bulletin of Bryansk state technical university 2017, no. 4 (November 8, 2017): 122–27. http://dx.doi.org/10.12737/article_5a02fa07c12da0.87522967.

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Crawford, Stuart L., and Barry M. Leiner. "VHP: An environment for the remote visualization of heuristic processes." Acta Astronautica 29, no. 7 (July 1993): 553–60. http://dx.doi.org/10.1016/0094-5765(93)90060-a.

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47

Trauwaert, E., and A. Decrock. "A heuristic algorithm for allocation of components in manufacturing processes." European Journal of Operational Research 31, no. 2 (August 1987): 232–39. http://dx.doi.org/10.1016/0377-2217(87)90027-0.

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Kiełczewski, Dariusz, Anna Matel, and Tomasz Poskrobko. "Project Management in Behavioural Perspective – Cognitive Biases in the Formulation of the Aim of the Project." Ekonomia i Zarzadzanie 8, no. 3 (September 1, 2016): 70–78. http://dx.doi.org/10.1515/emj-2016-0025.

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Abstract The article contains a behavioural analysis of the aim-formulating stage of the project. The purpose of the article is to point out that in the process of formulating the aim of the project, it comes to such decision-making situations which favour heuristic thinking. The article presents the results of the secondary research. As a result of verified theory, according to which in the process of formulating the aim of the project, the interference in decision-making processes may occur on the part of the heuristics and the resulting cognitive biases.

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Zarook, Yaser, Javad Rezaeian, Iraj Mahdavi, and Masoud Yaghini. "Efficient algorithms to minimize makespan of the unrelated parallel batch-processing machines scheduling problem with unequal job ready times." RAIRO - Operations Research 55, no. 3 (May 2021): 1501–22. http://dx.doi.org/10.1051/ro/2021062.

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This paper considers the minimization of makespan in the unrelated parallel batch processing machines scheduling problem with considering non-identical job size and dynamic job ready time. The considered unrelated machines have different capacity and different processing speed. Each machine processes a number of the jobs as a batch at the same time so that the machine’s capacity is not exceeded. The batch processing time and the batch ready time are equal to the largest processing time and the largest ready time of jobs in the same batch, respectively. In this paper, a Mixed Integer Linear Programming (MILP) model, two categories of the heuristic procedures (six heuristics) and a meta-heuristic algorithm are proposed to solve the problem. A lower bound is also presented by relaxing of the original problem to evaluate the quality of the proposed algorithms. The computational experiments show the performance of the proposed algorithms under the considered measures.

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Anuar, Wadi Khalid, Lai Soon Lee, Hsin-Vonn Seow, and Stefan Pickl. "A Multi-Depot Dynamic Vehicle Routing Problem with Stochastic Road Capacity: An MDP Model and Dynamic Policy for Post-Decision State Rollout Algorithm in Reinforcement Learning." Mathematics 10, no. 15 (July 30, 2022): 2699. http://dx.doi.org/10.3390/math10152699.

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In the event of a disaster, the road network is often compromised in terms of its capacity and usability conditions. This is a challenge for humanitarian operations in the context of delivering critical medical supplies. To optimise vehicle routing for such a problem, a Multi-Depot Dynamic Vehicle-Routing Problem with Stochastic Road Capacity (MDDVRPSRC) is formulated as a Markov Decision Processes (MDP) model. An Approximate Dynamic Programming (ADP) solution method is adopted where the Post-Decision State Rollout Algorithm (PDS-RA) is applied as the lookahead approach. To perform the rollout effectively for the problem, the PDS-RA is executed for all vehicles assigned for the problem. Then, at the end, a decision is made by the agent. Five types of constructive base heuristics are proposed for the PDS-RA. First, the Teach Base Insertion Heuristic (TBIH-1) is proposed to study the partial random construction approach for the non-obvious decision. The heuristic is extended by proposing TBIH-2 and TBIH-3 to show how Sequential Insertion Heuristic (SIH) (I1) as well as Clarke and Wright (CW) could be executed, respectively, in a dynamic setting as a modification to the TBIH-1. Additionally, another two heuristics: TBIH-4 and TBIH-5 (TBIH-1 with the addition of Dynamic Lookahead SIH (DLASIH) and Dynamic Lookahead CW (DLACW) respectively) are proposed to improve the on-the-go constructed decision rule (dynamic policy on the go) in the lookahead simulations. The results obtained are compared with the matheuristic approach from previous work based on PDS-RA.

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