Metaheuristics in combinatorial optimization: Overview and conceptual comparison

The field of metaheuristics for the application to combinatorial optimization problems is a rapidly growing field of research. This is due to the importance of combinatorial optimization problems for the scientific as well as the industrial world. We give a survey of the nowadays most important metaheuristics from a conceptual point of view. We outline the different components and concepts that are used in the different metaheuristics in order to analyze their similarities and differences. Two very important concepts in metaheuristics are intensification and diversification. These are the two forces that largely determine the behavior of a metaheuristic. They are in some way contrary but also complementary to each other. We introduce a framework, that we call the I&D frame, in order to put different intensification and diversification components into relation with each other. Outlining the advantages and disadvantages of different metaheuristic approaches we conclude by pointing out the importance of hybridization of metaheuristics as well as the integration of metaheuristics and other methods for optimization.

[1]  Michel Gendreau,et al.  A View of Local Search in Constraint Programming , 1996, CP.

[2]  R. Devaney An Introduction to Chaotic Dynamical Systems , 1990 .

[3]  Bart Selman,et al.  Systematic Versus Stochastic Constraint Satisfaction , 1995, IJCAI.

[4]  Cyril Fonlupt,et al.  Fitness Landscapes and Performance of Meta-Heuristics , 1999 .

[5]  Jörg Denzinger,et al.  On cooperation between evolutionary algorithms and other search paradigms , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[6]  G. P. McKeown,et al.  Optimization Software Class Libraries , 2002, Operations Research/Computer Science Interfaces Series.

[7]  Gerhard W. Dueck,et al.  Threshold accepting: a general purpose optimization algorithm appearing superior to simulated anneal , 1990 .

[8]  Feller William,et al.  An Introduction To Probability Theory And Its Applications , 1950 .

[9]  Patrick Prosser,et al.  Guided Local Search for the Vehicle Routing Problem , 1997 .

[10]  D. Fogel Evolutionary algorithms in theory and practice , 1997, Complex..

[11]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[12]  D. Goldberg,et al.  BOA: the Bayesian optimization algorithm , 1999 .

[13]  Edward P. K. Tsang,et al.  Guided local search and its application to the traveling salesman problem , 1999, Eur. J. Oper. Res..

[14]  Marco Tomassini,et al.  A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems , 1997, IEEE Trans. Evol. Comput..

[15]  Kalyanmoy Deb,et al.  Don't Worry, Be Messy , 1991, ICGA.

[16]  C. R. Reeves,et al.  Landscapes, operators and heuristic search , 1999, Ann. Oper. Res..

[17]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[18]  G. Dueck New optimization heuristics , 1993 .

[19]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[20]  J. Deneubourg,et al.  The self-organizing exploratory pattern of the argentine ant , 1990, Journal of Insect Behavior.

[21]  Lawrence J. Fogel,et al.  Intelligence Through Simulated Evolution: Forty Years of Evolutionary Programming , 1999 .

[22]  César Rego,et al.  Node-ejection chains for the vehicle routing problem: Sequential and parallel algorithms , 2001, Parallel Comput..

[23]  Fred W. Glover,et al.  Tabu Search , 1997, Handbook of Heuristics.

[24]  Michel Gendreau,et al.  A Constraint Programming Framework for Local Search Methods , 1999, J. Heuristics.

[25]  Toshihide Ibaraki,et al.  On metaheuristic algorithms for combinatorial optimization problems , 2001, Systems and Computers in Japan.

[26]  Gilbert Syswerda,et al.  Simulated Crossover in Genetic Algorithms , 1992, FOGA.

[27]  Marco Dorigo,et al.  HC-ACO: The Hyper-Cube Framework for Ant Colony Optimization , 2001 .

[28]  W. Vent,et al.  Rechenberg, Ingo, Evolutionsstrategie — Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. 170 S. mit 36 Abb. Frommann‐Holzboog‐Verlag. Stuttgart 1973. Broschiert , 1975 .

[29]  Michael D. Vose,et al.  The simple genetic algorithm - foundations and theory , 1999, Complex adaptive systems.

[30]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[31]  Federico Della Croce,et al.  A Recovering Beam Search algorithm for the one-machine dynamic total completion time scheduling problem , 2002, J. Oper. Res. Soc..

[32]  F. Glover HEURISTICS FOR INTEGER PROGRAMMING USING SURROGATE CONSTRAINTS , 1977 .

[33]  Renata M. Aiex,et al.  Parallel GRASP with path-relinking for job shop scheduling , 2003, Parallel Comput..

[34]  Nenad Mladenović,et al.  An Introduction to Variable Neighborhood Search , 1997 .

[35]  El-Ghazali Talbi,et al.  A Taxonomy of Hybrid Metaheuristics , 2002, J. Heuristics.

[36]  L. Darrell Whitley,et al.  The GENITOR Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best , 1989, ICGA.

[37]  David E. Goldberg,et al.  A Survey of Optimization by Building and Using Probabilistic Models , 2002, Comput. Optim. Appl..

[38]  Lawrence J. Fogel,et al.  Artificial Intelligence through Simulated Evolution , 1966 .

[39]  Thomas Stützle,et al.  Local search algorithms for combinatorial problems: analysis, algorithms, and new applications , 1999 .

[40]  F. Glover Scatter search and path relinking , 1999 .

[41]  Emile H. L. Aarts,et al.  4. Simulated annealing , 2003 .

[42]  Thomas Bäck,et al.  An Overview of Evolutionary Computation , 1993, ECML.

[43]  Wim Hordijk,et al.  A Measure of Landscapes , 1996, Evolutionary Computation.

[44]  M. Bernhard Introduction to Chaotic Dynamical Systems , 1992 .

[45]  F. Glover,et al.  Fundamentals of Scatter Search and Path Relinking , 2000 .

[46]  César Rego,et al.  Relaxed tours and path ejections for the traveling salesman problem , 1998, Eur. J. Oper. Res..

[47]  Hartmut Schmeck,et al.  Ant colony optimization for resource-constrained project scheduling , 2000, IEEE Trans. Evol. Comput..

[48]  Colin R. Reeves,et al.  Genetic Algorithms: Principles and Perspectives: A Guide to Ga Theory , 2002 .

[49]  Heinz Mühlenbein,et al.  Evolution in Time and Space - The Parallel Genetic Algorithm , 1990, FOGA.

[50]  V. W. Porto,et al.  Discovery of RNA structural elements using evolutionary computation. , 2002, Nucleic acids research.

[51]  Thomas Bäck,et al.  Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms , 1996 .

[52]  Charles E. Taylor Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. Complex Adaptive Systems.John H. Holland , 1994 .

[53]  A. E. Eiben,et al.  Genetic algorithms with multi-parent recombination , 1994, PPSN.

[54]  Thomas Stützle,et al.  The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances , 2003 .

[55]  José Luis González Velarde,et al.  Computing tools for modeling, optimization and simulation : interfaces in computer science and operations research , 2000 .

[56]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988 .

[57]  Olivier C. Martin,et al.  Combining simulated annealing with local search heuristics , 1993, Ann. Oper. Res..

[58]  Yves Crama,et al.  Local Search in Combinatorial Optimization , 2018, Artificial Neural Networks.

[59]  Cees H. M. van Kemenade Explicit Filtering of Building Blocks for Genetic Algorithms , 1996, PPSN.

[60]  Terry Jones,et al.  One Operator, One Landscape , 1995 .

[61]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[62]  Stefan Voß,et al.  Generic metaheuristics application to industrial engineering problems , 1999 .

[63]  David Connolly An improved annealing scheme for the QAP , 1990 .

[64]  Marco Dorigo,et al.  AntNet: Distributed Stigmergetic Control for Communications Networks , 1998, J. Artif. Intell. Res..

[65]  Stuart A. Kauffman,et al.  ORIGINS OF ORDER IN EVOLUTION: SELF-ORGANIZATION AND SELECTION , 1992 .

[66]  Wolfgang Christian,et al.  Dynamics of Complex Systems (Studies in Nonlinearity) , 1998 .

[67]  Luca Maria Gambardella,et al.  Ant Algorithms for Discrete Optimization , 1999, Artificial Life.

[68]  Ibrahim H. Osman,et al.  Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem , 1993, Ann. Oper. Res..

[69]  P. Stadler Landscapes and their correlation functions , 1996 .

[70]  Mauro Dell'Amico,et al.  On the Integration of Metaheuristic Strategies in Constraint Programming , 2005 .

[71]  Fred Glover,et al.  Scatter Search and Path Relinking: Advances and Applications , 2003, Handbook of Metaheuristics.

[72]  Lester Ingber,et al.  Adaptive simulated annealing (ASA): Lessons learned , 2000, ArXiv.

[73]  Yaneer Bar-Yam,et al.  Dynamics Of Complex Systems , 2019 .

[74]  Pierre Hansen,et al.  Variable neighborhood search: Principles and applications , 1998, Eur. J. Oper. Res..

[75]  Pedro Larrañaga,et al.  Estimation of Distribution Algorithms , 2002, Genetic Algorithms and Evolutionary Computation.

[76]  H. Mühlenbein,et al.  From Recombination of Genes to the Estimation of Distributions I. Binary Parameters , 1996, PPSN.

[77]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[78]  W. D. Harvey,et al.  Nonsystematic backtracking search , 1995 .

[79]  Marco Dorigo,et al.  The ant colony optimization meta-heuristic , 1999 .

[80]  Tad Hogg,et al.  Solving the Really Hard Problems with Cooperative Search , 1993, AAAI.

[81]  Andrea Schaerf,et al.  Combining Local Search and Look-Ahead for Scheduling and Constraint Satisfaction Problems , 1997, IJCAI.

[82]  Paul Shaw,et al.  Using Constraint Programming and Local Search Methods to Solve Vehicle Routing Problems , 1998, CP.

[83]  Andrea Lodi,et al.  Local Search and Constraint Programming , 2003, Handbook of Metaheuristics.

[84]  A. E. Eiben,et al.  On Evolutionary Exploration and Exploitation , 1998, Fundam. Informaticae.

[85]  Michael Vose The simple genetic algorithm: foundations and theory (complex adaptive systems) , 1999 .

[86]  Jan Karel Lenstra,et al.  Job Shop Scheduling by Simulated Annealing , 1992, Oper. Res..

[87]  Bart Selman,et al.  Heavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems , 2000, Journal of Automated Reasoning.

[88]  Shumeet Baluja,et al.  A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning , 1994 .

[89]  P. Hansen,et al.  Variable neighborhood search for the p-median , 1997 .

[90]  Steven David Prestwich,et al.  Combining the Scalability of Local Search with the Pruning Techniques of Systematic Search , 2002, Ann. Oper. Res..

[91]  Roberto Battiti,et al.  The Reactive Tabu Search , 1994, INFORMS J. Comput..

[92]  Jordan B. Pollack,et al.  Modeling Building-Block Interdependency , 1998, PPSN.

[93]  Mauricio G. C. Resende,et al.  Greedy Randomized Adaptive Search Procedures , 1995, J. Glob. Optim..

[94]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[95]  Edward P. K. Tsang,et al.  Guided Local Search for Solving SAT and Weighted MAX-SAT Problems , 2000, Journal of Automated Reasoning.

[96]  Pablo Moscato,et al.  Memetic algorithms: a short introduction , 1999 .

[97]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1967 .

[98]  Christian Blum Ant Colony Optimization For The Edge-weighted k-cardinality Tree Problem , 2002, GECCO.

[99]  Tad Hogg,et al.  Better Than The Best: The Power of Cooperation , 1993 .

[100]  El-Ghazali Talbi,et al.  COSEARCH: a co-evolutionary metaheuristic , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[101]  共立出版株式会社 コンピュータ・サイエンス : ACM computing surveys , 1978 .

[102]  Michel Gendreau,et al.  Metaheuristics in Combinatorial Optimization , 2022 .

[103]  E. Nowicki,et al.  A Fast Taboo Search Algorithm for the Job Shop Problem , 1996 .

[104]  Teodor Gabriel Crainic,et al.  Systemic Behavior of Cooperative Search Algorithms , 2002, Parallel Comput..

[105]  Mauricio G. C. Resende,et al.  Grasp: An Annotated Bibliography , 2002 .

[106]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988, Wiley interscience series in discrete mathematics and optimization.

[107]  Stuart A. Kauffman,et al.  The origins of order , 1993 .

[108]  Mauro Birattari,et al.  Model-Based Search for Combinatorial Optimization: A Critical Survey , 2004, Ann. Oper. Res..

[109]  Christian Blum,et al.  ACO Applied to Group Shop Scheduling: A Case Study on Intensification and Diversification , 2002, Ant Algorithms.

[110]  Teodor Gabriel Crainic,et al.  Parallel Strategies for Meta-Heuristics , 2003, Handbook of Metaheuristics.

[111]  Alain Hertz,et al.  A Taxonomy of Evolutionary Algorithms in Combinatorial Optimization , 1999, J. Heuristics.

[112]  Kenneth Steiglitz,et al.  Combinatorial Optimization: Algorithms and Complexity , 1981 .

[113]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

[114]  David S. Johnson,et al.  8. The traveling salesman problem: a case study , 2003 .

[115]  Zbigniew Michalewicz,et al.  Handbook of Evolutionary Computation , 1997 .

[116]  Pablo Moscato,et al.  On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms , 1989 .

[117]  A. E. Eiben,et al.  Constraint-satisfaction problems. , 2000 .

[118]  Silvano Martello,et al.  Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization , 2012 .

[119]  Paul A. Viola,et al.  MIMIC: Finding Optima by Estimating Probability Densities , 1996, NIPS.

[120]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[121]  Patrick Prosser,et al.  Solving Vehicle Routing Problems Using Constraint Programming and Metaheuristics , 2000, J. Heuristics.

[122]  David E. Goldberg,et al.  Genetic Algorithms with Sharing for Multimodalfunction Optimization , 1987, ICGA.

[123]  J. A. Lozano,et al.  Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation , 2001 .

[124]  Edward W. Felten,et al.  Large-Step Markov Chains for the Traveling Salesman Problem , 1991, Complex Syst..

[125]  Matthew L. Ginsberg,et al.  Limited Discrepancy Search , 1995, IJCAI.

[126]  Colin R. Reeves,et al.  Genetic Algorithms—Principles and Perspectives , 2002, Operations Research/Computer Science Interfaces Series.

[127]  David Joslin,et al.  "Squeaky Wheel" Optimization , 1998, AAAI/IAAI.

[128]  Michel Gendreau,et al.  METAHEURISTICS FOR THE VEHICLE ROUTING PROBLEM. , 1994 .

[129]  Roberto Battiti,et al.  Reactive search, a history-sensitive heuristic for MAX-SAT , 1997, JEAL.

[130]  Celso C. Ribeiro,et al.  Reactive GRASP: An Application to a Matrix Decomposition Problem in TDMA Traffic Assignment , 2000, INFORMS J. Comput..

[131]  Rafael Martí,et al.  GRASP and Path Relinking for 2-Layer Straight Line Crossing Minimization , 1999, INFORMS J. Comput..

[132]  G. Harik Linkage Learning via Probabilistic Modeling in the ECGA , 1999 .

[133]  Stefan Voß,et al.  Cooperative Intelligent Search Using Adaptive Memory Techniques , 1999 .

[134]  Fred W. Glover,et al.  Multi-level Cooperative Search: A New Paradigm for Combinatorial Optimization and an Application to Graph Partitioning , 1999, Euro-Par.

[135]  Mark Fleischer Simulated annealing: past, present, and future , 1995, WSC '95.

[136]  Bernd Freisleben,et al.  A genetic local search algorithm for solving symmetric and asymmetric traveling salesman problems , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[137]  Nicholas J. Radcliffe,et al.  Forma Analysis and Random Respectful Recombination , 1991, ICGA.

[138]  Mauro Birattari,et al.  Model-based Search for Combinatorial Optimization , 2001 .

[139]  Peter F. Stadler,et al.  Towards a theory of landscapes , 1995 .

[140]  Matthijs den Besten,et al.  Design of Iterated Local Search Algorithms , 2001, EvoWorkshops.

[141]  Tim Jones Evolutionary Algorithms, Fitness Landscapes and Search , 1995 .

[142]  Luca Maria Gambardella,et al.  An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem , 2000, INFORMS J. Comput..

[143]  Lawrence J. Fogel,et al.  Toward Inductive Inference Automata , 1962, IFIP Congress.

[144]  Rafael Martí,et al.  Intensification and diversification with elite tabu search solutions for the linear ordering problem , 1999, Comput. Oper. Res..

[145]  Zbigniew Michalewicz,et al.  Evolutionary computation techniques and their applications , 1997, 1997 IEEE International Conference on Intelligent Processing Systems (Cat. No.97TH8335).

[146]  Gilbert Laporte,et al.  Metaheuristics: A bibliography , 1996, Ann. Oper. Res..

[147]  Matthew L. Ginsberg,et al.  Dynamic Backtracking , 1993, J. Artif. Intell. Res..

[148]  Narendra Jussien,et al.  Local search with constraint propagation and conflict-based heuristics , 2000, Artif. Intell..

[149]  M. Dorigo,et al.  Design of Iterated Local Search Algorithms An Example Application to the Single Machine Total Weighted Tardiness Problem , 2001 .

[150]  M. Resende,et al.  A GRASP for graph planarization , 1997 .

[151]  Éric D. Taillard,et al.  Robust taboo search for the quadratic assignment problem , 1991, Parallel Comput..

[152]  Maurizio Lenzerini,et al.  LOCAL ++: A C++ framework for local search algorithms , 2000 .

[153]  Marco Dorigo,et al.  The hyper-cube framework for ant colony optimization , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[154]  Alistair I. Mees,et al.  Convergence of an annealing algorithm , 1986, Math. Program..

[155]  Teodor Gabriel Crainic,et al.  Introduction to the Special Issue on Parallel Meta-Heuristics , 2002, J. Heuristics.

[156]  C. Reeves Modern heuristic techniques for combinatorial problems , 1993 .

[157]  Fred W. Glover,et al.  An Experimental Evaluation of a Scatter Search for the Linear Ordering Problem , 2001, J. Glob. Optim..

[158]  Mauro Dell'Amico,et al.  Solution of the Cumulative Assignment Problem With a Well-Structured Tabu Search Method , 1999, J. Heuristics.

[159]  Marco Dorigo,et al.  Ant Colony Optimization and Stochastic Gradient Descent , 2002, Artificial Life.

[160]  Marco Dorigo,et al.  Optimization, Learning and Natural Algorithms , 1992 .

[161]  Celso C. Ribeiro,et al.  Variable neighborhood search for the degree-constrained minimum spanning tree problem , 2002, Discret. Appl. Math..

[162]  Kenneth Alan De Jong,et al.  An analysis of the behavior of a class of genetic adaptive systems. , 1975 .

[163]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[164]  Helena Ramalhinho Dias Lourenço,et al.  Iterated Local Search , 2001, Handbook of Metaheuristics.

[165]  David S. Johnson,et al.  Computers and In stractability: A Guide to the Theory of NP-Completeness. W. H Freeman, San Fran , 1979 .

[166]  Carlos A. Coello Coello,et al.  An updated survey of GA-based multiobjective optimization techniques , 2000, CSUR.

[167]  Manuel Laguna,et al.  Assigning Proctors to Exams with Scatter Search , 2001 .

[168]  Arantxa Etxeverria The Origins of Order , 1993 .

[169]  J. Lutton,et al.  Thermostatistical persistency: A powerful improving concept for simulated annealing algorithms , 1995 .

[170]  Fred W. Glover,et al.  Future paths for integer programming and links to artificial intelligence , 1986, Comput. Oper. Res..

[171]  David B. Fogel,et al.  An introduction to simulated evolutionary optimization , 1994, IEEE Trans. Neural Networks.

[172]  V. Cerný Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm , 1985 .

[173]  V. J. Rayward-Smith,et al.  Effective Local Search Techniques for the Steiner Tree Problem , 2000 .

[174]  Rich Caruana,et al.  Removing the Genetics from the Standard Genetic Algorithm , 1995, ICML.

[175]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[176]  H. Mühlenbein,et al.  Gene Pool Recombination in Genetic Algorithms , 1996 .

[177]  N. Mladenović,et al.  Variable neighborhood search for the k-cardinality tree , 2004 .

[178]  S. Binato,et al.  A GRASP FOR JOB SHOP SCHEDULING , 2001 .

[179]  Alain Hertz,et al.  A framework for the description of evolutionary algorithms , 2000, Eur. J. Oper. Res..

[180]  Ingo Rechenberg,et al.  Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .

[181]  Thomas Stützle,et al.  A beginner's introduction to iterated local search , 2001 .