A survey on optimization metaheuristics
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[1] F. Alajaji,et al. c ○ Copyright by , 1998 .
[2] Rudolf Paul Wiegand,et al. An analysis of cooperative coevolutionary algorithms , 2004 .
[3] Nikolaus Hansen,et al. Completely Derandomized Self-Adaptation in Evolution Strategies , 2001, Evolutionary Computation.
[4] Fernando José Von Zuben,et al. An Evolutionary Immune Network for Data Clustering , 2000, SBRN.
[5] Edward P. K. Tsang,et al. Applying an Extended Guided Local Search to the Quadratic Assignment Problem , 2003, Ann. Oper. Res..
[6] Risto Miikkulainen,et al. Competitive Coevolution through Evolutionary Complexification , 2011, J. Artif. Intell. Res..
[7] Fred W. Glover,et al. Scatter Search and Path Relinking : A Tutorial on the Linear Arrangement Problem , 2011, Int. J. Swarm Intell. Res..
[8] M. Brenner,et al. Physical mechanisms for chemotactic pattern formation by bacteria. , 1998, Biophysical journal.
[9] El-Ghazali Talbi,et al. Metaheuristics - From Design to Implementation , 2009 .
[10] H. Mühlenbein,et al. From Recombination of Genes to the Estimation of Distributions I. Binary Parameters , 1996, PPSN.
[11] M. Eaman. Immune system. , 2000, Nursing standard (Royal College of Nursing (Great Britain) : 1987).
[12] N. Metropolis,et al. Equation of State Calculations by Fast Computing Machines , 1953, Resonance.
[13] Chukwudi Anyakoha,et al. A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications , 2008, Natural Computing.
[14] Chunguo Wu,et al. Improved Bacterial Foraging Algorithms and Their Applications to Job Shop Scheduling Problems , 2007, ICANNGA.
[15] Janez Brest,et al. Self-adaptive differential evolution algorithm using population size reduction and three strategies , 2011, Soft Comput..
[16] Panta Lucic,et al. Computing with Bees: Attacking Complex Transportation Engineering Problems , 2003, Int. J. Artif. Intell. Tools.
[17] Xin Yao,et al. Hybridizing Cultural Algorithms and Local Search , 2006, Ideal.
[18] David H. Wolpert,et al. No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..
[19] Simon M. Garrett,et al. How Do We Evaluate Artificial Immune Systems? , 2005, Evolutionary Computation.
[20] T. Seeley,et al. Dancing bees tune both duration and rate of waggle-run production in relation to nectar-source profitability , 2000, Journal of Comparative Physiology A.
[21] Christos Koulamas,et al. A survey of simulated annealing applications to operations research problems , 1994 .
[22] Ali Karci. Imitation of Bee Reproduction as a Crossover Operator in Genetic Algorithms , 2004, PRICAI.
[23] David E. Goldberg,et al. The compact genetic algorithm , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).
[24] David Beasley,et al. An overview of Genetic Algorithms: Pt1, Fundamentals , 1993 .
[25] Nikolaus Hansen,et al. The CMA Evolution Strategy: A Comparing Review , 2006, Towards a New Evolutionary Computation.
[26] Chin-Teng Lin,et al. A Hybrid of Cooperative Particle Swarm Optimization and Cultural Algorithm for Neural Fuzzy Networks and Its Prediction Applications , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[27] Robert G. Reynolds,et al. The role of culture in the emergence of decision-making roles: An example using cultural algorithms , 2008 .
[28] R. Steele. Optimization , 2005 .
[29] Maurice Clerc,et al. The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..
[30] Thomas Bäck,et al. Evolutionary computation: Toward a new philosophy of machine intelligence , 1997, Complex..
[31] Yue Shi,et al. A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).
[32] Maurice Clerc,et al. Hybridization of Differential Evolution and Particle Swarm Optimization in a New Algorithm: DEPSO-2S , 2012, ICAISC.
[33] Israel A. Wagner,et al. Discrete bee dance algorithm for pattern formation on a grid , 2003, IEEE/WIC International Conference on Intelligent Agent Technology, 2003. IAT 2003..
[34] M. Resende. Metaheuristic Hybridization with Greedy Randomized Adaptive Search Procedures , 2008 .
[35] Dervis Karaboga,et al. AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .
[36] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[37] R. Storn,et al. Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .
[38] Carlos A. Coello Coello,et al. THEORETICAL AND NUMERICAL CONSTRAINT-HANDLING TECHNIQUES USED WITH EVOLUTIONARY ALGORITHMS: A SURVEY OF THE STATE OF THE ART , 2002 .
[39] Jacek Klinowski,et al. Taboo Search: An Approach to the Multiple Minima Problem , 1995, Science.
[40] Mauro Birattari,et al. Tuning Metaheuristics - A Machine Learning Perspective , 2009, Studies in Computational Intelligence.
[41] Jason Teo,et al. Self-adaptive population sizing for a tune-free differential evolution , 2009, Soft Comput..
[42] Panos M. Pardalos,et al. Global optimization by continuous grasp , 2007, Optim. Lett..
[43] Celso C. Ribeiro,et al. Greedy Randomized Adaptive Search Procedures , 2003, Handbook of Metaheuristics.
[44] M. Resende,et al. GRASP: Greedy Randomized Adaptive Search Procedures , 2003 .
[45] Jie Yao,et al. Using Competitive Co-evolution to Evolve Better Pattern Recognisers , 2005, Int. J. Comput. Intell. Appl..
[46] S. Luke,et al. When Coevolutionary Algorithms Exhibit Evolutionary Dyna mics , 2002 .
[47] Hans-Paul Schwefel,et al. Evolution strategies – A comprehensive introduction , 2002, Natural Computing.
[48] Gerhard W. Dueck,et al. Threshold accepting: a general purpose optimization algorithm appearing superior to simulated anneal , 1990 .
[49] Jonathan Timmis,et al. Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .
[50] Fernando José Von Zuben,et al. Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..
[51] Luca Maria Gambardella,et al. Adaptive memory programming: A unified view of metaheuristics , 1998, Eur. J. Oper. Res..
[52] Enrique Alba,et al. Parallel Metaheuristics: A New Class of Algorithms , 2005 .
[53] Ajith Abraham,et al. Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications , 2009, Foundations of Computational Intelligence.
[54] Oscar Castillo,et al. Human evolutionary model: A new approach to optimization , 2007, Inf. Sci..
[55] E. Baum. Towards practical `neural' computation for combinatorial optimization problems , 1987 .
[56] Thomas Stützle,et al. Classification of Metaheuristics and Design of Experiments for the Analysis of Components , 2001 .
[57] David B. Fogel,et al. Evolutionary Computation: Towards a New Philosophy of Machine Intelligence , 1995 .
[58] Kalyanmoy Deb,et al. A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.
[59] D. E. Goldberg,et al. Genetic Algorithms in Search , 1989 .
[60] D. Goldberg,et al. BOA: the Bayesian optimization algorithm , 1999 .
[61] Edward P. K. Tsang,et al. Guided local search and its application to the traveling salesman problem , 1999, Eur. J. Oper. Res..
[62] Mauro Brunato,et al. Reactive Search and Intelligent Optimization , 2008 .
[63] A survey of mutation techniques in genetic programming , 2006, GECCO '06.
[64] B. Suman,et al. A survey of simulated annealing as a tool for single and multiobjective optimization , 2006, J. Oper. Res. Soc..
[65] Peter J. Angeline,et al. Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences , 1998, Evolutionary Programming.
[66] Fred W. Glover,et al. Tabu Search for Nonlinear and Parametric Optimization (with Links to Genetic Algorithms) , 1994, Discret. Appl. Math..
[67] Röbbe Wünschiers,et al. An algorithmic approach to analyse genetic networks and biological energy production: an introduction and contribution where OR meets biology , 2009 .
[68] Shumeet Baluja,et al. A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning , 1994 .
[69] D Cvijovicacute,et al. Taboo search: an approach to the multiple minima problem. , 1995, Science.
[70] Johann Dréo,et al. Metaheuristics for Hard Optimization: Methods and Case Studies , 2005 .
[71] Hans-Paul Schwefel,et al. Evolution and optimum seeking , 1995, Sixth-generation computer technology series.
[72] Dervis Karaboga,et al. A survey: algorithms simulating bee swarm intelligence , 2009, Artificial Intelligence Review.
[73] Jose Luis Gonzalez-Velarde,et al. Chapter 10 GREEDY RANDOMIZED ADAPTIVE SEARCH PROCEDURES , .
[74] Gary B. Lamont,et al. Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation) , 2006 .
[75] Lothar Thiele,et al. A Comparison of Selection Schemes used in Genetic Algorithms , 1995 .
[76] Qingfu Zhang,et al. Population-Based Guided Local Search: Some preliminary experimental results , 2010, IEEE Congress on Evolutionary Computation.
[77] Robert G. Reynolds,et al. Using Cultural Algorithms to re-engineer Large-scale Semantic Networks , 2005, Int. J. Softw. Eng. Knowl. Eng..
[78] Haiping Ma,et al. An analysis of the equilibrium of migration models for biogeography-based optimization , 2010, Inf. Sci..
[79] Peter Goos,et al. Efficient GRASP+VND and GRASP+VNS metaheuristics for the traveling repairman problem , 2011, 4OR.
[80] Thomas Stützle,et al. The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances , 2003 .
[81] Günter Rudolph,et al. Contemporary Evolution Strategies , 1995, ECAL.
[82] Roberto Battiti,et al. The Reactive Tabu Search , 1994, INFORMS J. Comput..
[83] James Kennedy,et al. Particle swarm optimization , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.
[84] Xin-She Yang,et al. Engineering Optimizations via Nature-Inspired Virtual Bee Algorithms , 2005, IWINAC.
[85] Oscar Castillo,et al. Optimization of type-2 fuzzy systems based on bio-inspired methods: A concise review , 2012, Inf. Sci..
[86] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[87] Riccardo Poli,et al. Genetic Programming: An Introduction and Tutorial, with a Survey of Techniques and Applications , 2008, Computational Intelligence: A Compendium.
[88] Kevin M. Passino,et al. Bacterial Foraging Optimization , 2010, Int. J. Swarm Intell. Res..
[89] N. E. Collins,et al. Simulated annealing - an annotated bibliography , 1988 .
[90] D. Dasgupta. Artificial Immune Systems and Their Applications , 1998, Springer Berlin Heidelberg.
[91] Hans-Paul Schwefel,et al. Evolution and Optimum Seeking: The Sixth Generation , 1993 .
[92] J. Kennedy,et al. Population structure and particle swarm performance , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[93] Ville Tirronen,et al. Recent advances in differential evolution: a survey and experimental analysis , 2010, Artificial Intelligence Review.
[94] Abdullah Alsheddy,et al. Effective Application of Guided Local Search , 2010 .
[95] Alan S. Perelson,et al. Self-nonself discrimination in a computer , 1994, Proceedings of 1994 IEEE Computer Society Symposium on Research in Security and Privacy.
[96] Richard K. Belew,et al. New Methods for Competitive Coevolution , 1997, Evolutionary Computation.
[97] Michael Creutz,et al. Microcanonical Monte Carlo Simulation , 1983 .
[98] Christian Blum,et al. Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.
[99] John R. Koza,et al. Introduction to genetic programming , 1994, GECCO '07.
[100] Deborah M. Gordon. The organization of work in social insect colonies , 2002 .
[101] Leo Liberti,et al. Variable Neighbourhood Search for the Global Optimization of Constrained NLPs , 2006 .
[102] M. Clerc,et al. Particle Swarm Optimization , 2006 .
[103] Oliver Kramer,et al. A Review of Constraint-Handling Techniques for Evolution Strategies , 2010, Appl. Comput. Intell. Soft Comput..
[104] Kenneth Sörensen,et al. Adaptive and Multilevel Metaheuristics , 2008, Adaptive and Multilevel Metaheuristics.
[105] Mark Fleischer. Simulated annealing: past, present, and future , 1995, WSC '95.
[106] Jonathan Timmis,et al. On artificial immune systems and swarm intelligence , 2010, Swarm Intelligence.
[107] John A. Nelder,et al. A Simplex Method for Function Minimization , 1965, Comput. J..
[108] Uwe Aickelin,et al. The Danger Theory and Its Application to Artificial Immune Systems , 2008, ArXiv.
[109] P. Siarry,et al. Electronic component model minimization based on log simulated annealing , 1994 .
[110] Sean Luke,et al. A survey and comparison of tree generation algorithms , 2001 .
[111] Pascal Bouvry,et al. Particle swarm optimization: Hybridization perspectives and experimental illustrations , 2011, Appl. Math. Comput..
[112] Robert G. Reynolds,et al. Multi-objective Cultural Algorithms , 2010, IEEE Congress on Evolutionary Computation.
[113] Fred W. Glover,et al. A Template for Scatter Search and Path Relinking , 1997, Artificial Evolution.
[114] Craig A. Tovey,et al. On Honey Bees and Dynamic Server Allocation in Internet Hosting Centers , 2004, Adapt. Behav..
[115] Robert G. Reynolds,et al. Cultural algorithms: theory and applications , 1999 .
[116] Julie Greensmith,et al. The Deterministic Dendritic Cell Algorithm , 2008, ICARIS.
[117] Ajith Abraham,et al. Swarm Intelligence in Data Mining , 2009, Swarm Intelligence in Data Mining.
[118] Russell C. Eberhart,et al. A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.
[119] Oscar Castillo,et al. Bio-Inspired Optimization Methods for Minimization of Complex Mathematical Functions , 2011, MICAI.
[120] A. E. Eiben,et al. Evolutionary Programming VII , 1998, Lecture Notes in Computer Science.
[121] Thomas Bäck,et al. Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms , 1996 .
[122] Xin Yao,et al. Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..
[123] Michael Herdy,et al. Reproductive Isolation as Strategy Parameter in Hierarichally Organized Evolution Strategies , 1992, PPSN.
[124] Jian Cheng,et al. A novel multi-population cultural algorithm adopting knowledge migration , 2011, Soft Comput..
[125] D S Olton,et al. Spatial memory. , 1977, Scientific American.
[126] Jason Brownlee,et al. Clever Algorithms: Nature-Inspired Programming Recipes , 2012 .
[127] Rafael Martí,et al. Scatter Search: Diseño Básico y Estrategias avanzadas , 2002, Inteligencia Artif..
[128] Irène Charon,et al. The noising methods: A generalization of some metaheuristics , 2001, Eur. J. Oper. Res..
[129] M. Dorigo,et al. 1 Positive Feedback as a Search Strategy , 1991 .
[130] Kay Chen Tan,et al. A Competitive-Cooperative Coevolutionary Paradigm for Dynamic Multiobjective Optimization , 2009, IEEE Transactions on Evolutionary Computation.
[131] Liang Li,et al. Resolution of a Combinatorial Problem using Cultural Algorithms , 2009, J. Comput..
[132] Michèle Sebag,et al. Inductive Learning of Mutation Step-Size in Evolutionary Parameter Optimization , 1997, Evolutionary Programming.
[133] Jouni Lampinen,et al. A Fuzzy Adaptive Differential Evolution Algorithm , 2005, Soft Comput..
[134] Qingfu Zhang,et al. Combination of Guided Local Search and Estimation of Distribution Algorithm for Quadratic Assignment Problems , 2006 .
[135] Marco Dorigo,et al. Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.
[136] G. Harik. Linkage Learning via Probabilistic Modeling in the ECGA , 1999 .
[137] Yue Zhang,et al. BeeHive: An Efficient Fault-Tolerant Routing Algorithm Inspired by Honey Bee Behavior , 2004, ANTS Workshop.
[138] Thomas Stützle,et al. Local search algorithms for combinatorial problems - analysis, improvements, and new applications , 1999, DISKI.
[139] Francisco C. Santos,et al. Structure versus function: a topological perspective on immune networks , 2010, Natural Computing.
[140] Kevin M. Passino,et al. Biomimicry of bacterial foraging for distributed optimization and control , 2002 .
[141] Patrick Siarry,et al. Tabu Search applied to global optimization , 2000, Eur. J. Oper. Res..
[142] Luca Maria Gambardella,et al. A survey on metaheuristics for stochastic combinatorial optimization , 2009, Natural Computing.
[143] John Hallam,et al. Bee-havior in a mobile robot: the construction of a self-organized cognitive map and its use in robot navigation within a complex, natural environment , 1993, IEEE International Conference on Neural Networks.
[144] Mauricio G. C. Resende,et al. An annotated bibliography of GRASP-Part II: Applications , 2009, Int. Trans. Oper. Res..
[145] Mirjana Cangalovic,et al. General variable neighborhood search for the continuous optimization , 2006, Eur. J. Oper. Res..
[146] Thomas Bäck,et al. An Overview of Evolutionary Algorithms for Parameter Optimization , 1993, Evolutionary Computation.
[147] Enrique Alba,et al. A survey of parallel distributed genetic algorithms , 1999, Complex..
[148] Karl Sims,et al. Evolving 3d morphology and behavior by competition , 1994 .
[149] Jerne Nk. Towards a network theory of the immune system. , 1974 .
[150] David S. Johnson,et al. The Traveling Salesman Problem: A Case Study in Local Optimization , 2008 .
[151] Dan Simon,et al. Biogeography-Based Optimization , 2022 .
[152] Fabio A. González,et al. A comparative analysis of artificial immune network models , 2005, GECCO '05.
[153] W. Banzhaf,et al. Evolvability and Speed of Evolutionary Algorithms in Light of Recent Developments in Biology , 2010, Journal of Artificial Evolution and Applications.
[154] P. Hansen,et al. Variable neighbourhood search: methods and applications , 2010, Ann. Oper. Res..
[155] John R. Koza,et al. Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.
[156] Celso C. Ribeiro,et al. Reactive GRASP: An Application to a Matrix Decomposition Problem in TDMA Traffic Assignment , 2000, INFORMS J. Comput..
[157] Mike Preuss,et al. Experiments on metaheuristics: Methodological overview and open issues , 2007 .
[158] David B. Fogel,et al. System Identification Through Simulated Evolution: A Machine Learning Approach to Modeling , 1991 .
[159] David B. Fogel,et al. Meta-evolutionary programming , 1991, [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.
[160] Riccardo Poli,et al. A Field Guide to Genetic Programming , 2008 .
[161] Carlos A. Coello Coello,et al. A Cultural Algorithm with Differential Evolution to Solve Constrained Optimization Problems , 2004, IBERAMIA.
[162] Jonathan Timmis,et al. Theoretical advances in artificial immune systems , 2008, Theor. Comput. Sci..
[163] M. Beekman,et al. Honeybee Optimisation – An Overview and a New Bee Inspired Optimisation Scheme , 2011 .
[164] Julie Greensmith,et al. Malicious Code Execution Detection and Response Immune System inspired by the Danger Theory , 2010, ArXiv.
[165] Hussein A. Abbass,et al. A Survey of Probabilistic Model Building Genetic Programming , 2006, Scalable Optimization via Probabilistic Modeling.
[166] Ingo Rechenberg,et al. Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .
[167] Jonathan Timmis,et al. Application Areas of AIS: The Past, The Present and The Future , 2005, ICARIS.
[168] Ajith Abraham,et al. Particle Swarm Optimization: Performance Tuning and Empirical Analysis , 2009, Foundations of Computational Intelligence.
[169] Irène Charon,et al. Self-tuning of the noising methods , 2009 .
[170] Andries Petrus Engelbrecht,et al. A study of particle swarm optimization particle trajectories , 2006, Inf. Sci..
[171] Jonathan Timmis,et al. Application areas of AIS: The past, the present and the future , 2008, Appl. Soft Comput..
[172] Carlos A. Coello Coello,et al. Multi-Objective Optimization using Differential Evolution : A Survey of the State-ofthe-Art , 2008 .
[173] Marco Dorigo,et al. Optimization, Learning and Natural Algorithms , 1992 .
[174] Robert G. Reynolds,et al. The Effects of Generalized Reciprocal Exchange on the Resilience of Social Networks: An Example from the Prehispanic Mesa Verde Region , 2003, Comput. Math. Organ. Theory.
[175] Emma Hart,et al. Advances in artificial immune systems , 2011, Evol. Intell..
[176] David S. Johnson,et al. Local Optimization and the Traveling Salesman Problem , 1990, ICALP.
[177] Jonathan Timmis,et al. An interdisciplinary perspective on artificial immune systems , 2008, Evol. Intell..
[178] H A Scheraga,et al. An approach to the multiple-minima problem in protein folding by relaxing dimensionality. Tests on enkephalin. , 1987, Journal of molecular biology.
[179] Pierre Hansen,et al. Variable Neighborhood Search , 2018, Handbook of Heuristics.
[180] Amir Nakib,et al. Microscopic Image Segmentation with Two-dimensional Exponential Entropy Based on Hybrid Microcanonical Annealing , 2007, MVA.
[181] Chukwudi Anyakoha,et al. A review of particle swarm optimization. Part I: background and development , 2007, Natural Computing.
[182] Fred W. Glover,et al. Future paths for integer programming and links to artificial intelligence , 1986, Comput. Oper. Res..
[183] Karl Tuyls,et al. A bee algorithm for multi-agent systems: Recruitment and navigation combined , 2007 .
[184] V. Cerný. Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm , 1985 .
[185] Uday K. Chakraborty,et al. Advances in Differential Evolution , 2010 .
[186] Julie Greensmith,et al. Introducing Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomoly Detection , 2005, ICARIS.
[187] Ling Wang,et al. An effective co-evolutionary particle swarm optimization for constrained engineering design problems , 2007, Eng. Appl. Artif. Intell..
[188] R. Eberhart,et al. Empirical study of particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).
[189] Kenneth A. De Jong,et al. A Cooperative Coevolutionary Approach to Function Optimization , 1994, PPSN.
[190] Tim Blackwell,et al. Particle Swarm Optimization in Dynamic Environments , 2007, Evolutionary Computation in Dynamic and Uncertain Environments.
[191] Thomas Stützle,et al. Ant Colony Optimization and Swarm Intelligence , 2008 .
[192] Hans-Paul Schwefel,et al. Numerical optimization of computer models , 1981 .
[193] Thomas Stützle,et al. Ant colony optimization , 2006, IEEE Computational Intelligence Magazine.
[194] F. Ratnieks. Honeybee Democracy Thomas D. Seeley Honeybee Democracy , 2011, Animal Behaviour.
[195] David W. Coit,et al. Multi-objective optimization using genetic algorithms: A tutorial , 2006, Reliab. Eng. Syst. Saf..
[196] Hafiz Farooq Ahmad,et al. Using Honey Bee Teamwork Strategy in Software Agents , 2006, 2006 10th International Conference on Computer Supported Cooperative Work in Design.
[197] Oscar Castillo,et al. An improved evolutionary method with fuzzy logic for combining Particle Swarm Optimization and Genetic Algorithms , 2011, Appl. Soft Comput..
[198] Irène Charon,et al. The noising method: a new method for combinatorial optimization , 1993, Oper. Res. Lett..
[199] M. Resende,et al. A probabilistic heuristic for a computationally difficult set covering problem , 1989 .
[200] Mauricio G. C. Resende,et al. An annotated bibliography of GRASP - Part I: Algorithms , 2009, Int. Trans. Oper. Res..
[201] Fred Glover,et al. Scatter Search and Path Relinking: Advances and Applications , 2003, Handbook of Metaheuristics.
[202] David E. Goldberg,et al. A Survey of Optimization by Building and Using Probabilistic Models , 2002, Comput. Optim. Appl..
[203] Heinz Mühlenbein,et al. The Equation for Response to Selection and Its Use for Prediction , 1997, Evolutionary Computation.
[204] Sadan Kulturel-Konak,et al. A review of clonal selection algorithm and its applications , 2011, Artificial Intelligence Review.
[205] Y. Liu. Biomimicry of Social Foraging Bacteria for Distributed Optimization : Models , Principles , and Emergent Behaviors 1 , 2002 .
[206] David E. Goldberg,et al. Linkage Problem, Distribution Estimation, and Bayesian Networks , 2000, Evolutionary Computation.
[207] Jordan B. Pollack,et al. Co-Evolution in the Successful Learning of Backgammon Strategy , 1998, Machine Learning.
[208] M. Gendreau. Chapter 2 AN INTRODUCTION TO TABU SEARCH , 2005 .
[209] Riccardo Poli,et al. Analysis of the publications on the applications of particle swarm optimisation , 2008 .
[210] Kenneth A. De Jong,et al. Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents , 2000, Evolutionary Computation.
[211] Emile H. L. Aarts,et al. Simulated Annealing: Theory and Applications , 1987, Mathematics and Its Applications.
[212] Kay Chen Tan,et al. A distributed Cooperative coevolutionary algorithm for multiobjective optimization , 2006, IEEE Transactions on Evolutionary Computation.
[213] Carlos A. Coello Coello,et al. Cultural algorithms, an alternative heuristic to solve the job shop scheduling problem , 2007 .
[214] Nikolaus Hansen,et al. A Derandomized Approach to Self-Adaptation of Evolution Strategies , 1994, Evolutionary Computation.
[215] R. W. Dobbins,et al. Computational intelligence PC tools , 1996 .
[216] F. Glover. HEURISTICS FOR INTEGER PROGRAMMING USING SURROGATE CONSTRAINTS , 1977 .
[217] Lawrence J. Fogel,et al. Artificial Intelligence through Simulated Evolution , 1966 .
[218] Zhou Ji,et al. Revisiting Negative Selection Algorithms , 2007, Evolutionary Computation.
[220] Christian Blum,et al. Hybrid metaheuristics in combinatorial optimization: A survey , 2011, Appl. Soft Comput..
[221] Lothar Thiele,et al. A Comparison of Selection Schemes Used in Evolutionary Algorithms , 1996, Evolutionary Computation.
[222] Paul A. Viola,et al. MIMIC: Finding Optima by Estimating Probability Densities , 1996, NIPS.
[223] Pedro Larrañaga,et al. Research topics in discrete estimation of distribution algorithms based on factorizations , 2009, Memetic Comput..
[224] H A Abbass,et al. MARRIAGE IN HONEY-BEE OPTIMIZATION (MBO): A HAPLOMETROSIS POLYGYNOUS SWARMING APPROACH , 2001 .
[225] Thomas Bäck,et al. A Survey of Evolution Strategies , 1991, ICGA.
[226] Jonathan Timmis,et al. Artificial immune systems - a new computational intelligence paradigm , 2002 .
[227] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[228] J. A. Lozano,et al. Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation , 2001 .
[229] Edward W. Felten,et al. Large-Step Markov Chains for the Traveling Salesman Problem , 1991, Complex Syst..
[230] John Baxter,et al. Local Optima Avoidance in Depot Location , 1981 .
[231] Alex A. Freitas,et al. A survey of evolutionary algorithms for data mining and knowledge discovery , 2003 .
[232] Mauricio G. C. Resende,et al. Hybridizations of GRASP with Path-Relinking , 2013, Hybrid Metaheuristics.
[233] C. Gerhardt,et al. Carlos , 2011 .
[234] E. Tsang,et al. Guided Local Search , 2010 .
[235] Daniel Angus,et al. Multiple objective ant colony optimisation , 2009, Swarm Intelligence.
[236] Eugene L. Lawler,et al. Traveling Salesman Problem , 2009, Encyclopedia of Optimization.
[237] Thomas Stützle,et al. Ant Colony Optimization , 2009, EMO.
[238] Mauro Birattari,et al. Swarm Intelligence , 2012, Lecture Notes in Computer Science.
[239] R. Reynolds. AN INTRODUCTION TO CULTURAL ALGORITHMS , 2008 .
[240] H. Muhlenbein,et al. The Factorized Distribution Algorithm for additively decomposed functions , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).
[241] Robert G. Reynolds,et al. Multi-objective cultural algorithms , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).
[242] N K Jerne,et al. Towards a network theory of the immune system. , 1973, Annales d'immunologie.
[243] Hans-Georg Beyer,et al. Self-Adaptation in Evolutionary Algorithms , 2007, Parameter Setting in Evolutionary Algorithms.
[244] Xin Yao,et al. Fast Evolutionary Programming , 1996, Evolutionary Programming.
[245] P. N. Suganthan,et al. Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.
[246] Nenad Mladenovic,et al. Gaussian variable neighborhood search for continuous optimization , 2011, Comput. Oper. Res..
[247] Thomas Stützle,et al. Ant Colony Optimization: Overview and Recent Advances , 2018, Handbook of Metaheuristics.
[248] Thomas Stützle,et al. Ant colony optimization: artificial ants as a computational intelligence technique , 2006 .
[249] E. Ozcan,et al. Particle swarm optimization: surfing the waves , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).
[250] R. Menzel,et al. Spatial memory, navigation and dance behaviour in Apis mellifera , 2006, Journal of Comparative Physiology A.
[251] Xin Yao,et al. Evolutionary programming using mutations based on the Levy probability distribution , 2004, IEEE Transactions on Evolutionary Computation.
[252] K. Passino,et al. Biomimicry of Social Foraging Bacteria for Distributed Optimization: Models, Principles, and Emergent Behaviors , 2002 .
[253] Fernando Niño,et al. Recent Advances in Artificial Immune Systems: Models and Applications , 2011, Appl. Soft Comput..
[254] Irène Charon,et al. The Noising Methods: A Survey , 2002 .
[255] Mahmoud Melkemi,et al. Hybrid PSO-SA Type Algorithms for Multimodal Function Optimization and Reducing Energy Consumption in Embedded Systems , 2011, Appl. Comput. Intell. Soft Comput..
[256] Shumeet Baluja,et al. Using Optimal Dependency-Trees for Combinational Optimization , 1997, ICML.
[257] Nikolaus Hansen,et al. A restart CMA evolution strategy with increasing population size , 2005, 2005 IEEE Congress on Evolutionary Computation.
[258] W. Daniel Hillis,et al. Co-evolving parasites improve simulated evolution as an optimization procedure , 1990 .
[259] Alan S. Perelson,et al. The immune system, adaptation, and machine learning , 1986 .
[260] Nikolaus Hansen,et al. On the Adaptation of Arbitrary Normal Mutation Distributions in Evolution Strategies: The Generating Set Adaptation , 1995, ICGA.
[261] Olivier C. Martin,et al. Combining simulated annealing with local search heuristics , 1993, Ann. Oper. Res..
[262] P. H. Mills,et al. Extensions to Guided Local Search , 2002 .
[263] Marco Dorigo,et al. Ant colony optimization theory: A survey , 2005, Theor. Comput. Sci..
[264] C. Voudouris,et al. Guided Local Search — an Illustrative Example in Function Optimisation , 1998 .
[265] Julie Greensmith,et al. Detecting Danger: Applying a Novel Immunological Concept to Intrusion Detection Systems , 2010, ArXiv.
[266] S. Baluja,et al. Using Optimal Dependency-Trees for Combinatorial Optimization: Learning the Structure of the Search Space , 1997 .
[267] Fernando José Von Zuben,et al. omni-aiNet: An Immune-Inspired Approach for Omni Optimization , 2006, ICARIS.
[268] Uwe Aickelin,et al. Danger Theory: The Link between AIS and IDS? , 2003, ICARIS.
[269] Hans-Paul Schwefel,et al. Evolutionary Programming and Evolution Strategies: Similarities and Differences , 1993 .
[270] Carlos A. Coello Coello,et al. Multi-objective Optimization Using Differential Evolution: A Survey of the State-of-the-Art , 2008 .
[271] F. von Zuben,et al. An evolutionary immune network for data clustering , 2000, Proceedings. Vol.1. Sixth Brazilian Symposium on Neural Networks.
[272] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.
[273] Martin Pelikan,et al. An introduction and survey of estimation of distribution algorithms , 2011, Swarm Evol. Comput..
[274] Russell C. Eberhart,et al. A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.
[275] Wei Zhang,et al. A Survey of artificial immune applications , 2010, Artificial Intelligence Review.
[276] Robert G. Reynolds,et al. Knowledge-based solution to dynamic optimization problems using cultural algorithms , 2001 .
[277] Christian Blum,et al. Ant colony optimization: Introduction and recent trends , 2005 .
[278] Nubia Velasco,et al. GRASP/VND and multi-start evolutionary local search for the single truck and trailer routing problem with satellite depots , 2010, Eng. Appl. Artif. Intell..
[279] Hongfei Teng,et al. Cooperative Co-evolutionary Differential Evolution for Function Optimization , 2005, ICNC.
[280] Kenneth A. De Jong,et al. The effects of interaction frequency on the optimization performance of cooperative coevolution , 2006, GECCO.
[281] Leandro Nunes de Castro,et al. aiNet: An Artificial Immune Network for Data Analysis , 2002 .
[282] A. Gupta,et al. SWAN: A Swarm Intelligence Based Framework for Network Management of IP Networks , 2007, International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007).
[283] M Reyes Sierra,et al. Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art , 2006 .
[284] Andries Petrus Engelbrecht,et al. Fundamentals of Computational Swarm Intelligence , 2005 .
[285] Carlos A. Coello Coello,et al. Adding Knowledge And Efficient Data Structures To Evolutionary Programming: A Cultural Algorithm For Constrained Optimization , 2002, GECCO.
[286] Sung Hoon Jung,et al. Queen-bee evolution for genetic algorithms , 2003 .
[287] Peter A. Whigham,et al. Grammar-based Genetic Programming: a survey , 2010, Genetic Programming and Evolvable Machines.
[288] Amit Konar,et al. Swarm Intelligence Algorithms in Bioinformatics , 2008, Computational Intelligence in Bioinformatics.
[289] Andrew W. Shogan,et al. Semi-greedy heuristics: An empirical study , 1987 .
[290] M. Pelikán,et al. The Bivariate Marginal Distribution Algorithm , 1999 .
[291] Carlos Cotta,et al. Adaptive and multilevel metaheuristics , 2008 .