Journal articles: 'Evolutional strategy'

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Ding, Yangke, Lei Ma, Ye Zhang, and Dingzhong Feng. "Analysis of Evolution Mechanism and Optimal Reward-Penalty Mechanism for Collection Strategies in Reverse Supply Chains: The Case of Waste Mobile Phones in China." Sustainability 10, no. 12 (December 12, 2018): 4744. http://dx.doi.org/10.3390/su10124744.

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The aim of this paper is to discuss the coopetition (cooperative competition) relationship between a manufacturer and a collector in the collection of waste mobile phones (WMPs) and examine the evolution mechanism and the internal reward-penalty mechanism (RPM) for their collection strategies. A coopetition evolutionary game model based on evolutionary game theory was developed to obtain their common and evolutional collection strategies. The pure-strategy Nash equilibriums of this model were obtained which showed their collection strategy choices of perfect competition or cooperation. The mixed strategy Nash equilibrium was obtained which revealed evolution trends and laws. In addition, the optimal RPM was obtained in the sensitivity analysis of related parameters. The example of WMPs in China was taken to examine the simulation of the RPM. Results show that (i) although the manufacturer and the collector may change their strategies of cooperation and competition over time, cooperation is their best choice to increase payoffs; (ii) the optimal RPM is beneficial to propel their cooperation tendency and then to increase their payoffs.

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Yao, Kong, Bong Yang, Xing Zu Wang, and Chang Qing Gao. "Pedigree Based Product Conceptual Design." Applied Mechanics and Materials 215-216 (November 2012): 597–601. http://dx.doi.org/10.4028/www.scientific.net/amm.215-216.597.

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By applying pedigree into product conceptual structure design, an evolutionary conceptual design approach is set forth to make full use of creative and innovative intelligence of living systems for design automation. According to the evolutional logic of quantities to quality, the relationship between different conceptual structures is deduced and ordered，then is expressed as product pedigree. The classification description model of product pedigree is established, which can be used as unified functionally isomorphic model during the intelligent conceptual design process. On the other hand, according to the evolutional logic of quality to quantities, pedigree based product evolutionary design strategy are given. Based on the relation network among pedigree units, multiple variation designing schemes can be obtained, which is a strong backbone to the innovative design process. Finally, design examples are used to demonstrate the successful application of the proposed pedigree based evolutionary method in the multi-scheme conceptual design of product.

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Wang, Xing Zu, Bo Yang, Kong Yao, and Chang Qing Gao. "Product Pedigree Based Conceptual Structure Evolutionary Design." Applied Mechanics and Materials 215-216 (November 2012): 612–15. http://dx.doi.org/10.4028/www.scientific.net/amm.215-216.612.

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By applying biological pedigree concept into product conceptual structure design, an conceptual structural design approach is set forth to make full use of creative and innovative intelligence of living systems for design automation. According to the relationship between different product structures with same function, the classification model of product pedigree is established, which can be used as unified functional isomorphic model during the intelligent conceptual design process. On the other hand, according to the evolutional logic from quality change to quantities change, pedigree based product evolutionary design strategy is given. Product pedigrees which are homology dependent are used as basic evolutionary models, based on which, the parameter based, interaction field based and interaction mater based evolutional conceptual design method are proposed, respectively. Based on the relation network of the pedigree units, multiple variant design schemes can be obtained, which is a strong backbone to the innovative design process. Finally, design examples are used to demonstrate the successful application of the proposed pedigree based evolutionary method in the product variant design.

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Smirnov, Sergei Vladimirovich. "STRATEGY OF SOCIO-BIO-ECO-CO-EVOLUTIONAL DEVELOPMENT: ESSENTIAL ASPECTS, BACKGROUNDS FOR REALIZATION." Manuscript, no. 9 (September 2019): 106–11. http://dx.doi.org/10.30853/manuscript.2019.9.21.

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Tanimizu, Y., T. Sakaguchi, K. Iwamura, and N. Sugimura. "Evolutional reactive scheduling for agile manufacturing systems." International Journal of Production Research 44, no. 18-19 (September 15, 2006): 3727–42. http://dx.doi.org/10.1080/00207540600791632.

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Gaweiler, Andrey. "The methodology of the gradual implementation of development strategy in urban economy under the shifts in technology bases." Moscow University Economics Bulletin 2015, no. 6 (December 31, 2015): 40–57. http://dx.doi.org/10.38050/01300105201563.

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On the basis of the identified critical insufficiency of a widespread extrapolation approach to the development strategy of the Russian city we synthesize a stepwise process of long-term economic development of the city through changing technological bases, represented as a chain of successive steps of the main strategic decision makers. The resulting trajectory of economic development of the city is presented in the form of regular replacement of long-term waves of radical innovations through restructuring crises. The proposed integrated strategic approach, synthesizing macro- and microeconomic evolutional approaches deriving from the fields of business, finance, management, strategy, municipal and state regulation can help all the participants of the transition process to innovative path of development, which adds to the leading role of a city in the context of globalization.

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Li, Qian, and Yuanfei Kang. "Knowledge Sharing Willingness and Leakage Risk: An Evolutional Game Model." Sustainability 11, no. 3 (January 23, 2019): 596. http://dx.doi.org/10.3390/su11030596.

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Prior research of knowledge sharing between firms mainly focuses on enabling factors, such as benefits resulting from knowledge sharing, leading to an overlook at barriers. Guided by transaction cost economics and social exchange theory, our study constructed an evolutional game model to analyse the dynamic evolution process of the firm’s knowledge sharing behaviour in a setting of supply chain networks. Using a simulation in our game model, we firstly reveal how a long-term strategy for supply chain partners towards knowledge sharing is determined through reaching an equilibrium between enabling factors (revenue gained in various forms) and impeding factors (knowledge leakage) in a dynamic process. Secondly, our analysis demonstrates that the competition or rivalry side of the “co-opetition” relationship acts as the major barrier for knowledge sharing due to the sharer’s concern of knowledge leakage. Thirdly, our model has identified knowledge relevancy as the inherent property of knowledge and the firm’ ability of knowledge inference as two important factors influencing knowledge leakage.

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Moriwaki, Toshimichi, and Keiichi Shirase. "Intelligent machine tools: current status and evolutional architecture." International Journal of Manufacturing Technology and Management 9, no. 3/4 (2006): 204. http://dx.doi.org/10.1504/ijmtm.2006.010055.

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Gao, Wu. "Nonlinear Forecasting Model regarding Evolutional Risk of the PPP Project." Journal of Advanced Transportation 2018 (October 14, 2018): 1–9. http://dx.doi.org/10.1155/2018/3870285.

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The special topic of this paper is to build a nonlinear measuring model between PPP project risk and multiple variables and test it through case analysis. Nonlinear regression method was used in this research to study the risk mutation of public-private partnership (PPP) projects without any significant events. Risk evolution is influenced by three factors which include (1) macroscopic environment, (2) micro environment, and (3) subject’s capacity and their cooperative relationship. First, it reveals three main drive variables of project risk evolution through case analysis. Second, it builds a nonlinear time-varying measurement model which is then transformed to a classical regression model. Lastly, it estimates and tests the model parameter by an example. The study shows that there is an integral negative correlation among the three independent variables within a certain threshold range, revealing macro environment as the most significant factor of project risk. Analyzing the complex relationship between multiple impact variables and risk evolution of PPP projects can provide a basic tool for forecasting and control of risk.

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Wang, Xing Wei, Yong Jian Sun, Wei Gang Hou, Min Huang, and Lei Guo. "A Novel Static Traffic Grooming Algorithm Based on Steady Elimination Evolutionary and Gaming." Advanced Materials Research 403-408 (November 2011): 1869–74. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.1869.

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In this paper, we propose a static traffic grooming method, where both wavelength layered graph and evaluation function are deployed with the objective of maximizing Quality of Service (QoS) satisfaction degree of user and minimizing comparative cost of IP over WDM optical networks, based on Steady Elimination Evolutionary Algorithm (SEEA) and gaming. Using proposed novel hybridization operation and evolutional strategy with the consideration of individual diversity in niche population, our method can eliminate the worst individual in the current niche population and generate optimized traffic grooming program. Our method has been analyzed and compared with the other traffic grooming schemes on the realistic network topologies in our simulations. Simulation results have demonstrated that our method outperforms state-of-the-art grooming schemes, which is highly feasible and effective.

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Yuan, Jiawei, Hai-Lin Liu, and Chaoda Peng. "Population Decomposition-Based Greedy Approach Algorithm for the Multi-Objective Knapsack Problems." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 04 (February 2, 2017): 1759006. http://dx.doi.org/10.1142/s0218001417590066.

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Despite the effectiveness of the decomposition-based multi-objective evolutional algorithm (MOEA/D-M2M) in solving continuous multi-objective optimization problems (MOPs), its performance in addressing 0/1 multi-objective knapsack problems (MOKPs) has not been fully explored. In this paper, we use MOEA/D-M2M with an improved greedy repair strategy to solve MOKPs. It first decomposes an MOKP into a number of simple optimization subproblems and solves them in a collaborative way. Each subproblem has its own subpopulation, and then an improved greedy strategy is introduced to improve the performance of the proposed algorithm on MOKPs. Therein, a weight vector chosen randomly from a corresponding subpopulation is utilized to repair infeasible individuals or improve feasible individuals to have a better fitness, which improves the convergence of the population. Experimental studies on a set of test instances indicate that the MOEA/D-M2M with the improved greedy strategy is superior to MOGLS and MOEA/D in terms of finding better approximations to the Pareto front.

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Zhang, Yiqun, Peijie Lin, Zhicong Chen, and Shuying Cheng. "A Population Classification Evolution Algorithm for the Parameter Extraction of Solar Cell Models." International Journal of Photoenergy 2016 (2016): 1–16. http://dx.doi.org/10.1155/2016/2174573.

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To quickly and precisely extract the parameters for solar cell models, inspired by simplified bird mating optimizer (SBMO), a new optimization technology referred to as population classification evolution (PCE) is proposed. PCE divides the population into two groups, elite and ordinary, to reach a better compromise between exploitation and exploration. For the evolution of elite individuals, we adopt the idea of parthenogenesis in nature to afford a fast exploitation. For the evolution of ordinary individuals, we adopt an effective differential evolution strategy and a random movement of small probability is added to strengthen the ability to jump out of a local optimum, which affords a fast exploration. The proposed PCE is first estimated on 13 classic benchmark functions. The experimental results demonstrate that PCE yields the best results on 11 functions by comparing it with six evolutional algorithms. Then, PCE is applied to extract the parameters for solar cell models, that is, the single diode and the double diode. The experimental analyses demonstrate that the proposed PCE is superior when comparing it with other optimization algorithms for parameter identification. Moreover, PCE is tested using three different sources of data with good accuracy.

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Yanagisawa, Hideyoshi, and Shuichi Fukuda. "Design optimisation for customers' KANSEI requirement: application of interactive reduct evolutional computation to industrial design with curves." International Journal of Manufacturing Technology and Management 10, no. 4 (2007): 360. http://dx.doi.org/10.1504/ijmtm.2007.012155.

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Du, Jia Xing, Shao Hui Miao, Bin Zhao, and Hong Yun Li. "Improved Ant Colony Algorithm and its Application to the Parameter Optimization in Rainstorm Intensity Formula." Applied Mechanics and Materials 108 (October 2011): 111–15. http://dx.doi.org/10.4028/www.scientific.net/amm.108.111.

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Ant Colony Algorithm (ACA) is a kind of excellent algorithm which solves the problem of combination optimization. However, there are a great many difficulties when the ACA is used to solve the problems of continuous optimization directly. In the paper, the author tries to introduce the evolutional strategy of the variable domain search item in order to improve the ACA. The improved ACA is applied to solving the continuous problems such as the parameter optimization in rainstorm intensity formula. The result which is compared with the results of other optimizing algorithms shows that the improved ACA can be used to solve the parameter optimization in rainstorm intensity formula. Moreover, the rainstorm intensity formula which is obtained the optimizing parameters by all kinds of optimizing algorithms is compared with the effect of fitting initial data. It is better than other optimizing methods. Ant algorithm is a new bionic algorithm which is put forward by Italian academician, Dorigo, et al. The academicians are inspired by the result which people studied the real ant colony behavior in nature[a-b]. The ant colony in nature finds out finally the shortest route from the nest to the food source by information exchange and cooperation each other when they search for the food in nature. According to the similarity between the Travelling Salesman Problem (TSP) and the process, Dorigo et al. solves the TSP at last by releasing “man-made ant”. Subsequently, the ACA obtains a successful application in a series of combinatorial optimizing problems such as job-shop dispatching problem, assigning problem and sequential ordering. These applications show the superiority of the ACA in finding the solutions to the complicated discrete optimizing problems. However, the continuous optimizing problem is different from the combinatorial one. What to find the solutions to the continuous optimizing problems needs that the algorithm can produce its new solution in the continuous solution space in order to find out the most excellent one while the ACA itself doesn’t have the function. Therefore, there are a lot of difficulties to find the solution to continuous optimizing problem directly[c-e]. On the basis of deep study for a great many algorithms which are applied to continuous optimizing problem, the author tries to introduce the evolutional strategy into the ACA and expects that the improved ACA is used to solve the continuous optimizing problem. And the excellent algorithm is introduced to the meteorological fields to solve a number of continuous optimizing problems.

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Le, Phuoc Huu. "Identification of colonial economic heritage in the southern part of Vietnam." Science and Technology Development Journal 16, no. 3 (September 30, 2013): 140–51. http://dx.doi.org/10.32508/stdj.v16i3.1654.

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As the first mass of land in Vietnam becoming a French colony, Nam Ky – the Southern part of Vietnam (currently renamed Nam Bo – the South of Vietnam) was affected, earliest and hardest, by the consequences of colonialism. Brutal governance mechanism; plundering ruses to fully exploit profit; policies of enslavement, for obscurantism, and cultural intoxication; etc. are all sinful acts and evil nature of colonialism which the Vietnamese people as well as the entire advanced humankind have fought against and eradicated. However, it would be full of prejudices, non-objective and one-sided to totally deny important impacts for the evolutional process of the nation’s history in a number of economic sectors that the colonial exploitation has brought, if temporarily excluding its driving force and purpose. Therefore, study of the process, characteristics and consequences of the policy to exploit colonies in the Southern part of Vietnam is to contribute to sound recognition of historical heritages during colonial times, also to better understand our socio-economic starting point 100 years, more or less, ago; so as to reach proper selection and inheritance in the mission of fostering industrialization and modernization for and towards today’s sustainable development strategy.

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Kasthurirathna, Dharshana, Mahendra Piraveenan, and Shahadat Uddin. "Evolutionary Stable Strategies In Networked Games: The Influence Of Topology." Journal of Artificial Intelligence and Soft Computing Research 5, no. 2 (April 1, 2015): 83–95. http://dx.doi.org/10.1515/jaiscr-2015-0021.

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Abstract Evolutionary game theory is used to model the evolution of competing strategies in a population of players. Evolutionary stability of a strategy is a dynamic equilibrium, in which any competing mutated strategy would be wiped out from a population. If a strategy is weak evolutionarily stable, the competing strategy may manage to survive within the network. Understanding the network-related factors that affect the evolutionary stability of a strategy would be critical in making accurate predictions about the behaviour of a strategy in a real-world strategic decision making environment. In this work, we evaluate the effect of network topology on the evolutionary stability of a strategy. We focus on two well-known strategies known as the Zero-determinant strategy and the Pavlov strategy. Zero-determinant strategies have been shown to be evolutionarily unstable in a well-mixed population of players. We identify that the Zero-determinant strategy may survive, and may even dominate in a population of players connected through a non-homogeneous network. We introduce the concept of ‘topological stability’ to denote this phenomenon. We argue that not only the network topology, but also the evolutionary process applied and the initial distribution of strategies are critical in determining the evolutionary stability of strategies. Further, we observe that topological stability could affect other well-known strategies as well, such as the general cooperator strategy and the cooperator strategy. Our observations suggest that the variation of evolutionary stability due to topological stability of strategies may be more prevalent in the social context of strategic evolution, in comparison to the biological context.

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Zhang, Ting-He, and Shao-Wu Zhang. "Advances in the Prediction of Protein Subcellular Locations with Machine Learning." Current Bioinformatics 14, no. 5 (June 28, 2019): 406–21. http://dx.doi.org/10.2174/1574893614666181217145156.

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Background: Revealing the subcellular location of a newly discovered protein can bring insight into their function and guide research at the cellular level. The experimental methods currently used to identify the protein subcellular locations are both time-consuming and expensive. Thus, it is highly desired to develop computational methods for efficiently and effectively identifying the protein subcellular locations. Especially, the rapidly increasing number of protein sequences entering the genome databases has called for the development of automated analysis methods. Methods: In this review, we will describe the recent advances in predicting the protein subcellular locations with machine learning from the following aspects: i) Protein subcellular location benchmark dataset construction, ii) Protein feature representation and feature descriptors, iii) Common machine learning algorithms, iv) Cross-validation test methods and assessment metrics, v) Web servers. Result & Conclusion: Concomitant with a large number of protein sequences generated by highthroughput technologies, four future directions for predicting protein subcellular locations with machine learning should be paid attention. One direction is the selection of novel and effective features (e.g., statistics, physical-chemical, evolutional) from the sequences and structures of proteins. Another is the feature fusion strategy. The third is the design of a powerful predictor and the fourth one is the protein multiple location sites prediction.

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Imura, Tomoko, Fumito Kawakami, Nobu Shirai, and Masaki Tomonaga. "Perception of the average size of multiple objects in chimpanzees ( Pan troglodytes )." Proceedings of the Royal Society B: Biological Sciences 284, no. 1861 (August 23, 2017): 20170564. http://dx.doi.org/10.1098/rspb.2017.0564.

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Humans can extract statistical information, such as the average size of a group of objects or the general emotion of faces in a crowd without paying attention to any individual object or face. To determine whether summary perception is unique to humans, we investigated the evolutional origins of this ability by assessing whether chimpanzees, which are closely related to humans, can also determine the average size of multiple visual objects. Five chimpanzees and 18 humans were able to choose the array in which the average size was larger, when presented with a pair of arrays, each containing 12 circles of different or the same sizes. Furthermore, both species were more accurate in judging the average size of arrays consisting of 12 circles of different or the same sizes than they were in judging the average size of arrays consisting of a single circle. Our findings could not be explained by the use of a strategy in which the chimpanzee detected the largest or smallest circle among those in the array. Our study provides the first evidence that chimpanzees can perceive the average size of multiple visual objects. This indicates that the ability to compute the statistical properties of a complex visual scene is not unique to humans, but is shared between both species.

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Wang, Bill, Yuanfei Kang, Paul Childerhouse, and Baofeng Huo. "Interpersonal and inter-organizational relationship drivers of supply chain integration." Industrial Management & Data Systems 118, no. 6 (July 9, 2018): 1170–91. http://dx.doi.org/10.1108/imds-05-2017-0216.

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Purpose The purpose of this paper is to examine how interpersonal relationships (IPRs) and inter-organisational relationships (IORs) interact with each other as driving forces of supply chain integration (SCI). More specifically (the) three dimensions of IPR – personal affection, personal credibility, and personal communication – are examined in regards to how they affect inter-organisational relationships during SCI. Design/methodology/approach The research employed an exploratory multiple case study approach with four New Zealand case companies selected as the empirical basis. Data were collected through semi-structured interviews of managerial executives in relation to supply chain activities, which were triangulated with company archival data. Findings The authors found that IPRs are able to interact with IORs to influence the integration of supply chains. More specifically, IPRs influence IORs by initiating organisational relationships in the SCI context; and influences from IPR dimensions on IORs tend to be of differing magnitudes and have different evolutional paths across the whole SCI process. Originality/value This research contributes to knowledge about the roles and mechanisms through which IPRs shape and enable inter-organisational level relationships within the SCI context.

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Ray-Mukherjee, Jayanti, and Shomen Mukherjee. "Evolutionary stable strategy." Resonance 21, no. 9 (September 2016): 803–14. http://dx.doi.org/10.1007/s12045-016-0386-5.

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Huang, Minshui, and Yongzhi Lei. "Bearing Damage Detection of a Reinforced Concrete Plate Based on Sensitivity Analysis and Chaotic Moth-Flame-Invasive Weed Optimization." Sensors 20, no. 19 (September 25, 2020): 5488. http://dx.doi.org/10.3390/s20195488.

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This article proposes a novel damage detection method based on the sensitivity analysis and chaotic moth-flame-invasive weed optimization (CMF-IWO), which is utilized to simultaneously identify the damage of structural elements and bearings. First, the sensitivity coefficients of eigenvalues to the damage factors of structural elements and bearings are deduced, the regularization technology is used to solve the problem of equation undetermined, meanwhile, the modal strain energy-based index is utilized to detect the damage locations, and the regularization objective function is constructed to quantify the damage severity. Then, for the subsequent procedure of damage detection, CMF-IWO is proposed based on moth-flame optimization and invasive weed optimization as well as chaos theory, reverse learning, and evolutional strategy. The optimization effectiveness of the hybrid algorithm is verified by five benchmark functions and a damage identification numerical example of a simply supported beam; the results demonstrate it is of great global search ability and higher convergence efficiency. After that, a numerical example of an 8-span continuous beam and an experimental reinforced concrete plate are both adopted to evaluate the proposed damage identification method. The results of the numerical example indicate that the proposed method can locate and quantify the damage of structural elements and bearings with high accuracy. Furthermore, the outcomes of the experimental example show that despite the existence of some errors and uncertain factors, the method still obtains an acceptable result. Generally speaking, the proposed method is proved that it is of good feasibility.

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Pan, Jichao, Yan Cai, Liang Wang, Akiko Maehara, Gary S. Mintz, Dalin Tang, and Zhiyong Li. "A prediction tool for plaque progression based on patient-specific multi-physical modeling." PLOS Computational Biology 17, no. 3 (March 29, 2021): e1008344. http://dx.doi.org/10.1371/journal.pcbi.1008344.

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Atherosclerotic plaque rupture is responsible for a majority of acute vascular syndromes and this study aims to develop a prediction tool for plaque progression and rupture. Based on the follow-up coronary intravascular ultrasound imaging data, we performed patient-specific multi-physical modeling study on four patients to obtain the evolutional processes of the microenvironment during plaque progression. Four main pathophysiological processes, i.e., lipid deposition, inflammatory response, migration and proliferation of smooth muscle cells (SMCs), and neovascularization were coupled based on the interactions demonstrated by experimental and clinical observations. A scoring table integrating the dynamic microenvironmental indicators with the classical risk index was proposed to differentiate their progression to stable and unstable plaques. The heterogeneity of plaque microenvironment for each patient was demonstrated by the growth curves of the main microenvironmental factors. The possible plaque developments were predicted by incorporating the systematic index with microenvironmental indicators. Five microenvironmental factors (LDL, ox-LDL, MCP-1, SMC, and foam cell) showed significant differences between stable and unstable group (p < 0.01). The inflammatory microenvironments (monocyte and macrophage) had negative correlations with the necrotic core (NC) expansion in the stable group, while very strong positive correlations in unstable group. The inflammatory microenvironment is strongly correlated to the NC expansion in unstable plaques, suggesting that the inflammatory factors may play an important role in the formation of a vulnerable plaque. This prediction tool will improve our understanding of the mechanism of plaque progression and provide a new strategy for early detection and prediction of high-risk plaques.

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Uli, Vincenzo. "Co-evolutionary dynamics in the music industry." International Journal of Organizational Analysis 26, no. 2 (May 14, 2018): 296–311. http://dx.doi.org/10.1108/ijoa-10-2016-1073.

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Purpose What effects does radical innovation produce on the dialectical relationship between enterprises and their environment? In this paper, by adopting the dynamic adaptation matrix methodological framework, the author addresses this research question by discussing the evolution of the music industry in the period of 1999-2013. The purpose of this study is to identify possible co-evolutionary adaptation paths, namely, virtuous or contradictory adaptation cycles. Design/methodology/approach The paper is presented as a descriptive comparative case study about the major changes that have occurred in the sector, and this could be of interest to the industry stakeholders. The paper also contributes to the debate about co-evolution as it is an empirical implementation of the adaptation matrix and sheds light on the main environmental dynamics. Findings The author found that for a low level of environmental determinism and moderate degree of strategic choice, cost leadership strategy dominates other strategic options. For moderate levels of environmental determinism, differentiation-marketing strategy ensures a better performance than differentiation-innovation strategy. Finally, for a high level of both environmental determinism and strategic choice, differentiation-innovation strategy is the best strategic option among differentiation strategies. Practical implications The adaptation matrix, especially in its dynamic form, can be applied to understand the changes within a sector with a co-evolutionary lens and to analyze critically the strategic choices enacted by the market’s incumbents. Originality/value This study may have useful implications for both scientific research and managerial practice. In fact, it is intended for all scholars and practitioners interested in exploring the nature of organizational adaptation, especially in industries affected by major technological changes, such as the music industry, which only recently has been considered as a fertile ground for research.

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Zhang, Mo, Chaoran Lin, Jun Guan, and Yan Lin. "The Effects of Open Innovation Platform Knowledge Strategies on Participants: Evolutionary Game Research." Mathematical Problems in Engineering 2020 (September 16, 2020): 1–12. http://dx.doi.org/10.1155/2020/4012713.

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Based on previous research on open innovation and appropriability strategies, using knowledge production functions and evolutionary game methods, this paper describes the process of dynamic cooperation between open innovation platforms and their participants. This paper specifically analyzes the influence of open innovation platform’s knowledge appropriability/knowledge sharing strategies, as well as participants’ exit/nonexit strategy, on the cooperative relationship. Through simulation analysis, this paper draws the following conclusions: first, the knowledge appropriability strategy of the open innovation platform and the participant’s nonexit strategy is an important strategic point of the cooperation between open innovation platforms and participants; second, the amount of knowledge production affects the strategic choices of open innovation platforms, while the knowledge increment affects the strategic choices of participants; third, the appreciation coefficient of complementary assets determines the direction of evolution of the cooperation process.

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Song, Qiusheng, Peng Jiang, and Song Zheng. "Application of Evolutionary Game Theory in Safety Management of Chemical Production." Processes 8, no. 4 (April 16, 2020): 472. http://dx.doi.org/10.3390/pr8040472.

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The chemical industry is essential in the social economy, and the issue of production safety has aroused widespread concern. Chemical safety incidents occupy the headlines from time to time, and chemical production safety management is particularly important. This paper presents an application model based on evolutionary game theory in the assessment and analysis of chemical production safety management. The model uses evolutionary game theory to construct a strategic interactive payoff matrix between the management department of a chemical plant and the chemical plant using a replicated dynamic equation to analyze their strategic interaction and to reveal the evolution of behavioral strategy selection. The evolution results were verified and simulated. The application of this model provides an effective safety management basis and recommendations for the management of chemical plants, providing a foundation for the safe production and healthy development of chemical plants.

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Manral, Lalit. "An evolutionary theory of demand-side determinants of strategy dynamics." Management Research Review 41, no. 3 (March 19, 2018): 314–44. http://dx.doi.org/10.1108/mrr-08-2017-0249.

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Purpose This paper aims to explain how the dynamic demand environment influences strategic firm behavior along an industry’s evolutionary path. A conceptual gap concerning the influence of demand-side environmental factors (vis-à-vis changes in technology and policy) on firms’ strategic choices motivates the theory developed herein. The paper’s contribution to the literature on “evolutionary perspective in strategy” also addresses an important gap in the emerging literature on “strategy dynamics”. Design/methodology/approach The conceptual framework in this paper features a dynamic demand environment that provides the structural context for firms’ strategic choices. It conceptualizes demand-side competence as a mediating firm-specific construct to explain the endogenous relationship between the characteristics of the demand environment and firms’ path dependent demand-side investments. Findings A review of the literature on evolutionary perspective in strategy reveals an important conceptual gap concerning the structural determinants of dynamic firm behavior. There is no explanation of the endogenous relationship between dynamic demand structure, firms’ dynamic demand-side competence, and temporally heterogeneous strategic choices. Originality/value The demand-side explanation of how idiosyncratic firm behavior is endogenously determined, with both structural characteristics (demand structure) and firm competences (demand-side competence), addresses an important conceptual gap. The novelty of the theory developed herein lies in its explication of the effect of dynamic demand environment on the evolution of idiosyncratic strategic firm behavior – entry, investment and exit – along the evolutionary path of an industry. The theory developed herein not only explains the effect of both determinants of idiosyncratic strategic firm behavior – the external industry environment (dynamic market structure) and internal firm environment (dynamic firm competences) – but also explains how the determinants evolve along the industry’s lifecycle.

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Schendel, Dan. "Evolutionary perspectives on strategy." Strategic Management Journal 17, S1 (July 5, 2007): 1–4. http://dx.doi.org/10.1002/smj.4250171002.

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Barnett, William P., and Robert A. Burgelman. "Evolutionary perspectives on strategy." Strategic Management Journal 17, S1 (July 5, 2007): 5–19. http://dx.doi.org/10.1002/smj.4250171003.

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Li, Kangshun, Fahui Gu, Wei Li, and Ying Huang. "A Dual-Population Evolutionary Algorithm Adapting to Complementary Evolutionary Strategy." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 01 (October 11, 2018): 1959004. http://dx.doi.org/10.1142/s0218001419590043.

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Optimization problems widely exist in scientific research and engineering practice, which have been one of the research hotshots and difficulties in intelligent computing. The single swarm intelligence optimization algorithms often show such defects as searching stagnation, low accuracy of convergence, part optimum and poor generalization ability when facing the increasingly sophisticated optimization problems. In the study of multiple population, the choice of evolution strategy often has great influence on the performance of the algorithm, and this paper puts forward a kind of dual-population evolutionary algorithm adapting to complementary evolutionary strategy (DPCEDT) based on the study of differential evolution algorithm, teaching and learning-based optimization algorithm. The simulation results show that the algorithm performs better than the TLBO-DE, HDT and DPDT and some other algorithms do in most test functions. It suggests that the complementary evolutionary strategies are more advantageous than other evolutionary strategies in dual-population evolutionary algorithms.

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Methe, David T., Tadao Kagono, Ikujiro Nonaka, Kiyonori Sakakibara, Akihiro Okumura, Shiori Sakamoto, and Johnny K. Johansson. "Strategic vs. Evolutionary Management: A U.S.-Japan Comparison of Strategy and Organization." Administrative Science Quarterly 32, no. 3 (September 1987): 450. http://dx.doi.org/10.2307/2392917.

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Sanderson, Stephen K. "Evolutionary Materialism: A Theoretical Strategy for the Study of Social Evolution." Sociological Perspectives 37, no. 1 (March 1994): 47–73. http://dx.doi.org/10.2307/1389409.

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Existing approaches to the study of social evolution are insufficient for the task of explaining the full range of social evolution from the Neolithic Revolution down to the present day. Some anthropological approaches shed considerable light on the evolution of preindustrial and precapitalist societies but are less capable of explaining the evolution of the modern world. Sociological approaches usually have the opposite result: they shed light on the evolution of the modern world but falter with respect to premodern times. This article presents a comprehensive formal-propositional theoretical approach to social evolution that combines the strengths of anthropological and sociological approaches while minimizing their weaknesses. The theoretical approach offered, referred to as evolutionary materialism, comprises propositions concerned with the directional nature of world history, the substance or content of social evolution, the principal causal factors in social evolution, the adaptational character of social evolution, the interplay of agency and structure in social evolution, the units of social evolution, the pace of social evolution, and methods of studying social evolution. The second half of the article attempts a brief logical and empirical justification of evolutionary materialism.

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Su, Chao, Li Tao Zhang, and Peng Fei Liu. "The Matching and Evolutionary Path Model of IT and Business Alignment Based on Dynamic Capabilities." Applied Mechanics and Materials 519-520 (February 2014): 1463–67. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.1463.

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The good match of IT and business is an important prerequisite to ensure business strategy and the value of enterprise information investments. With the intensive application of IT and the rapidly changing of environment, the match of IT and business should be more concerned about its dynamic characteristics and evolution law. Based on the research analysis of IT and business matching, the strategic alignment model (SAM model) and the business-IT strategic alignment maturity model (LAM model), the paper introduces the dynamic capabilities to build an IT and business matching and evolutionary path model under the action of dynamic capabilities. In the model, nine paths and four steps are proposed to describe the matching and evolution of IT and business. The roles of dynamic capabilities are explained in describing the matching and evolution paths, such as perception, capital-and technology path dependence, learning, dynamic feedback, resource restructuring and reconfiguration, team, coordination and innovation etc. It has a strong reference to the deep research of IT and business alignment, matching and evolutionary path and the enterprise information technology applications.

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VUK, PAVEL. "EVOLUCIJA POJMA STRATEGIJE IN NJEGOVO POVEZOVANJE S POLITIKO." CONTEMPORARY MILITARY CHALLENGES, ISSUE VOLUME 2021/ISSUE 23/1 (May 14, 2021): 15–28. http://dx.doi.org/10.33179/bsv.99.svi.11.cmc.23.1.1.

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V prispevku na podlagi zgodovinskega in kritičnega pristopa različnih pomembnejših teoretikov k razvoju strategije pojasnjujemo evolucijo pojma strategije, zlasti pa, zakaj in kako je njegov pomen povezan s človekovo naravo in tudi političnim vedenjem. Spoznanja raziskave kažejo dvoje, in sicer, da se je v zgodnjem zgodovinskem obdobju strategija snovala predvsem zaradi človekovih potreb po varnosti, v sodobni strateški misli, ko je ta potreba prerasla v širše politično vprašanje družbe, pa se je razumevanje strategije vse bolj povezovalo s politiko in njenim vplivom na proces oblikovanja in uresničevanja strategije. Ključne besede strategija, taktika, politika. Abstract Based on the historical and critical approaches of various important theorists to the development of strategy, this paper aims to explain the evolution of the concept of strategy, especially why and how its meaning is related to the human nature and the political behaviour. The research has shown two things. Firstly, that in the early historical period the strategy was designed mainly due to the human need for security, and, secondly, that in the modern strategic thought when these needs grew into a broader political issue of the society, the understanding of strategy was increasingly being related to the politics and its impact on the design and implementation of strategy. Key words strategy, tactics, politics.

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Vlados, Charis. "The Stra.Tech.Man Scorecard." International Journal of Business Administration 12, no. 2 (February 23, 2021): 36. http://dx.doi.org/10.5430/ijba.v12n2p36.

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This article presents the “Stra.Tech.Man approach” (strategy-technology-management synthesis) as the basis for creating a “Stra.Tech.Man Scorecard,” which can be used for the strategic audit of every socio-economic organization. After reviewing the literature on strategic control and strategic audit, the study proceeds with a critical appraisal of Kaplan and Norton’s balanced scorecard model and presents the theoretical foundations of the Stra.Tech.Man approach. It composes a first conceptual outline of the Stra.Tech.Man Scorecard, which can function as an integrated monitoring tool, exploring and describing the evolution of “physiologies” of the studied socio-economic organizations (firms). It concludes that the formal balanced scorecard approach: (a) has been applied mainly to larger and more sophisticated organizations, (b) does not offer a compound understanding of the central dimensions of strategy, technology, and management that can be linked in an integrated way to the financial results, (c) leaves relatively unspecified many critical aspects of a firm’s choices, especially in strategy articulation, technology selection, and management implementation, (d) does not create complete profiles for the firms’ evolutionary physiologies. In contrast, the Stra.Tech.Man Scorecard: (i) does not have as a prerequisite any pre-existing systematic performance measurement framework in the organization and, therefore, it is not limited by any firm size, type, or physiology, (ii) it links in an evolutionary way the “core” qualitative dimensions of strategy, technology and management (Stra.Tech.Man audit) with the quantitative financial results of the organization, (iii) it can and has been used as an integrated analysis instrument by taking into account more adequately the evolutionary dimensions of the meso-environment of organizations besides the micro-level of analysis which the balanced scorecard is primarily associated.

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Hou, Wei, HongBin Dong, and GuiSheng Yin. "Co-Evolutionary Algorithms Based on Mixed Strategy." Journal of Information Technology Research 4, no. 2 (April 2011): 17–30. http://dx.doi.org/10.4018/jitr.2011040102.

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Inspired by evolutionary game theory, this paper modifies previous mixed strategy framework, adding a new mutation operator and extending to crossover operation, and proposes co-evolutionary algorithms based on mixed crossover and/or mutation strategy. The mixed mutation strategy set consists of Gaussian, Cauchy, Levy, single point and differential mutation operators; the mixed crossover strategy set consists of cuboid, two-points and heuristic crossover operators. The novel algorithms automatically select crossover and/or mutation operators from a given mixed strategy set, and improve the evolutionary performance by dynamically utilizing the most effective operator at different stages of evolution. The proposed algorithms are tested on a set of 21 benchmark problems. The results show that the new mixed strategies perform equally well or better than the best of the previous evolutionary methods for all of the benchmark problems. The proposed MMCGA has shown significant superiority over others.

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Smith, Eric Alden. "Endless forms: human behavioural diversity and evolved universals." Philosophical Transactions of the Royal Society B: Biological Sciences 366, no. 1563 (February 12, 2011): 325–32. http://dx.doi.org/10.1098/rstb.2010.0233.

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Human populations have extraordinary capabilities for generating behavioural diversity without corresponding genetic diversity or change. These capabilities and their consequences can be grouped into three categories: strategic (or cognitive), ecological and cultural-evolutionary. Strategic aspects include: (i) a propensity to employ complex conditional strategies, some certainly genetically evolved but others owing to directed invention or to cultural evolution; (ii) situations in which fitness payoffs (or utilities) are frequency-dependent, so that there is no one best strategy; and (iii) the prevalence of multiple equilibria, with history or minor variations in starting conditions (path dependence) playing a crucial role. Ecological aspects refer to the fact that social behaviour and cultural institutions evolve in diverse niches, producing various adaptive radiations and local adaptations. Although environmental change can drive behavioural change, in humans, it is common for behavioural change (especially technological innovation) to drive environmental change (i.e. niche construction). Evolutionary aspects refer to the fact that human capacities for innovation and cultural transmission lead to diversification and cumulative cultural evolution; critical here is institutional design, in which relatively small shifts in incentive structure can produce very different aggregate outcomes. In effect, institutional design can reshape strategic games, bringing us full circle.

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Thorne McAlister, Debbie, and Linda Ferrell. "The role of strategic philanthropy in marketing strategy." European Journal of Marketing 36, no. 5/6 (June 1, 2002): 689–705. http://dx.doi.org/10.1108/03090560210422952.

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Outlines the concept of strategic philanthropy, assesses its development and evolution, gives examples of the stakeholder focus, discusses marketing issues and addresses elements to consider in implementation. Organizations have long realized the benefits of benevolent philanthropy in supporting community, employees and the interests of investors. It has only been in recent years that organizations have formalized and integrated the philanthropic decisions with corporate citizenship and other key strategic organizational performance‐related decisions. Organizations in the twenty‐first century are increasingly concerned about managing societal issues in marketing to benefit key stakeholder interests. A new definition of strategic philanthropy is developed and contrasted with other initiatives that link marketing and society. Finally, suggestions for future research are provided.

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Zhang, Ming Ming, Shu Guang Zhao, and Xu Wang. "Discrete Differential Evolution Strategy and its Numerical Application." Key Engineering Materials 439-440 (June 2010): 540–45. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.540.

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Differential evolution is a simple but powerful parallel global search optimization algorithm, which has been successfully used to solve single-objective optimization problems. In this paper, a novel discrete differential evolution strategy (D2E) is proposed to enhance the ability of solving the numerical optimization problems. D2E adopts the difference information from the binary evolutionary individuals and self-adaptive parameter adjustment to effectively explore the global solution space. The results of numerical simulations demonstrate that the proposed strategy is feasible and efficient, has the better metrics performances.

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Lindstedt, Carita, and Mikael Mokkonen. "The Evolutionary Strategy of Deception." Current Zoology 60, no. 1 (February 1, 2014): 1–5. http://dx.doi.org/10.1093/czoolo/60.1.1.

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Zhao, Yi, Dong Li, and Liqiang Pan. "Cooperation or Competition: An Evolutionary Game Study between Commercial Banks and Big Data-Based E-Commerce Financial Institutions in China." Discrete Dynamics in Nature and Society 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/890972.

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On the premise of participants’ bounded rationality and information asymmetry, this paper focuses on the cooperation or competition relationship between Chinese e-commerce financial institutions and commercial banks from the perspective of dynamic game. Theoretical mathematical model is built to analyze an evolutionary stable strategy under different conditions. We adopt real-life data set collected in Alibaba’s network credit loan business case and Jingdong’s supply chain financing business case to verify the evolution process of cooperation and competition relationship. The results show that (cooperation, cooperation) is bound to be the evolutionary stable strategy (ESS) and cooperation tends to be increasingly in-depth and expansive for commercial banks as well as e-commerce financial institutions in China. The complementarity of participants’ core competitiveness is explored as the root of cooperation. Finally, strategic suggestions are put forward on cooperation between e-commerce financial institutions and commercial banks.

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Yan, Hui, Haixiang Wei, and Min Wei. "Exploring Tourism Recovery in the Post-COVID-19 Period: An Evolutionary Game Theory Approach." Sustainability 13, no. 16 (August 16, 2021): 9162. http://dx.doi.org/10.3390/su13169162.

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This study aims to explore the process of tourism recovery in the post-COVID-19 period and the role of stakeholders in promoting such a process. Using evolutionary game theory, this study analyzes the behavior interactions and game equilibrium of stakeholders in the development of tourism by constructing an evolutionary game model amongst governments, tourists and tourism enterprises. Then, the influences of different evolution paths and major parameters affecting stakeholders’ strategy selection are discussed. With the aim of illustrating the role of the stakeholders in the tourism sector’s economic recovery under the impact of the coronavirus pandemic, the numerical experiment was conducted using the MATLAB 2016 software. The results show that the development and change of the emergent public health events affect tourism stakeholders’ behavior strategy. Moreover, the strategic choices of each player, including governments, tourism enterprises and tourists, are also constantly evolving at different stages of the pandemic.

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Rivers, Alena. "Talking Strategy: A Look at ALSC’s Strategic Plan 2017–2020." Children and Libraries 16, no. 3 (September 24, 2018): 32. http://dx.doi.org/10.5860/cal.16.3.32.

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In February 2017, the Association for Library Service to Children (ALSC) adopted a three-year strategic plan for 2017–2020, which is the framework to direct how ALSC will invest its valuable and limited resources in meeting the future needs of its members and influencing the evolution of the profession.

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Zhang, Yong Qiang, and Jing Xiao. "Population Diversity Strategy in Gene Expression Programming." Advanced Materials Research 204-210 (February 2011): 288–92. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.288.

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Population diversity is one of the most important factors that influence the convergence speed and evolution efficiency of gene expression programming (GEP) algorithm. In this paper, the population diversity strategy of GEP (GEP-PDS) is presented, inheriting the advantage of superior population producing strategy and various population strategy, to increase population average fitness and decrease generations, to make the population maintain diversification throughout the evolutionary process and avoid “premature” to ensure the convergence ability and evolution efficiency. The simulation experiments show that GEP-PDS can increase the population average fitness by 10% in function finding, and decrease the generations for convergence to the optimal solution by 30% or more compared with other improved GEP.

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VIGNOLO, THIERRY. "REPUTATION BY IMITATION: AN EVOLUTIONARY MODEL WITH STRATEGIC MATCHING." International Game Theory Review 08, no. 03 (September 2006): 417–28. http://dx.doi.org/10.1142/s0219198906000990.

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This paper shows how strategic matching generates reputation-building behavior in an evolutionary chain-store game. Strategic matching means the possibility for an entrant to choose in a strategic way the local market into which it will move. Players are boundedly rational and follow behavioral rules simply requiring that the frequency of any strategy enjoying the highest payoff should never decrease. In preventing the random entries in markets of "fighting monopolists", strategic matching reinforces the reputation effects. Using the bounded rationality set-up offered by evolutionary game theory, the paper follows Selten (1978)'s intuition underlying the necessity of a limited rationality approach in order to capture reputation effects.

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Guo, Weiwei. "Collaborative knowledge management for corporate ecological responsibility." Data Technologies and Applications 53, no. 3 (July 1, 2019): 304–17. http://dx.doi.org/10.1108/dta-01-2019-0003.

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Purpose Knowledge has become the basis of enhancing the core competitiveness of enterprises in this era of knowledge-driven economies. Collaborative knowledge management not only realizes the real-time exchange and communication of knowledge among different enterprises, but also facilitates the collaboration and integration of knowledge. Collaborative knowledge management has been successfully applied to different fields. To address the poor ecological responsibility of enterprises, the purpose of this paper is to introduce the concept of collaborative knowledge management in this research to determine if the evolution of the decision-making process in collaborative knowledge management is involved in corporate ecological responsibility (CER). Design/methodology/approach This research established an evolutionary game model of collaborative knowledge management for CER. The behavioral, evolutionary law and stable behavioral, evolutionary strategy of the participants was identified according to the replicator dynamics equation. Simulation analysis was conducted using MATLAB software. Findings Research results demonstrated that, first, the strategic selection of firms is influenced by cost and interest coefficients. Second, the strategy, selection of enterprises, is related to the common benefits of enterprise cooperation. Third, during the systematic evolution and stabilization of strategies, enterprises adopt the same knowledge strategies. Originality/value On the basis of the research findings, policy suggestions were proposed to encourage enterprises to implement collaborative knowledge management strategies in ecological responsibility.

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Burgelman, Robert A. "A Process model of strategic business exit: Implications for an evolutionary perspective on strategy." Strategic Management Journal 17, S1 (July 5, 2007): 193–214. http://dx.doi.org/10.1002/smj.4250171012.

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ZHENG Ye. "The Study on Government Innovation Strategy based on Evolutionary Game Analysis and Evolutionary Stable Strategy." Journal of Convergence Information Technology 7, no. 18 (October 31, 2012): 456–63. http://dx.doi.org/10.4156/jcit.vol7.issue18.55.

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DING, FEI, YUN LIU, and YONG LI. "CO-EVOLUTION OF OPINION AND STRATEGY IN PERSUASION DYNAMICS: AN EVOLUTIONARY GAME THEORETICAL APPROACH." International Journal of Modern Physics C 20, no. 03 (March 2009): 479–90. http://dx.doi.org/10.1142/s0129183109013728.

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In this paper, a new model of opinion formation within the framework of evolutionary game theory is presented. The model simulates strategic situations when people are in opinion discussion. Heterogeneous agents adjust their behaviors to the environment during discussions, and their interacting strategies evolve together with opinions. In the proposed game, we take into account payoff discount to join a discussion, and the situation that people might drop out of an unpromising game. Analytical and emulational results show that evolution of opinion and strategy always tend to converge, with utility threshold, memory length, and decision uncertainty parameters influencing the convergence time. The model displays different dynamical regimes when we set differently the rule when people are at a loss in strategy.

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Zhang Guiyang, 张贵阳, 霍炬 Huo Ju, 杨明 Yang Ming, 周婞 Zhou Xing, 魏亮 Wei Liang, and 薛牧遥 Xue Muyao. "基于双更新策略加权差分进化粒子群的双目相机标定." Infrared and Laser Engineering 50, no. 4 (2021): 20200280. http://dx.doi.org/10.3788/irla20200280.

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Wang and Shi. "An Evolutionary Game Model for Industrial Pollution Management under Two Punishment Mechanisms." International Journal of Environmental Research and Public Health 16, no. 15 (August 3, 2019): 2775. http://dx.doi.org/10.3390/ijerph16152775.

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In recent years, with the rapid development of the economy, industrial pollution problems have become more and more serious. This paper constructs an evolutionary game model for industrial pollution between the local governments and enterprises to study the dynamic evolution path of a game system and the evolutionary stable strategy under two punishment mechanisms. The results show that, in a static punishment mechanism (SPM), the strategy between governments and enterprises is uncertain. Moreover, the evolutionary trajectory between governments and enterprises is uncertain. However, under the dynamic punishment mechanism (DPM), the evolution path between governments and enterprises tends to converge to a stable value. Thus, the DPM is more conducive than the SPM for industrial pollution control.

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Journal articles on the topic 'Evolutional strategy'

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