Using multi-objective evolutionary algorithms for single-objective optimization

In recent decades, several multi-objective evolutionary algorithms have been successfully applied to a wide variety of multi-objective optimization problems. Along the way, several new concepts, paradigms and methods have emerged. Additionally, some authors have claimed that the application of multi-objective approaches might be useful even in single-objective optimization. Thus, several guidelines for solving single-objective optimization problems using multi-objective methods have been proposed. This paper offers a survey of the main methods that allow the use of multi-objective schemes for single-objective optimization. In addition, several open topics and some possible paths of future work in this area are identified.

[1]  Xiaodong Li,et al.  Evolutionary algorithms and multi-objectivization for the travelling salesman problem , 2009, GECCO.

[2]  Peter J. Fleming,et al.  On the Evolutionary Optimization of Many Conflicting Objectives , 2007, IEEE Transactions on Evolutionary Computation.

[3]  Carlos A. Coello Coello,et al.  Handling Constraints in Genetic Algorithms Using Dominance-based Tournaments , 2002 .

[4]  Jing J. Liang,et al.  Dynamic Multi-Swarm Particle Swarm Optimizer with a Novel Constraint-Handling Mechanism , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[5]  Carlos A. Coello Coello,et al.  Constraint-handling in nature-inspired numerical optimization: Past, present and future , 2011, Swarm Evol. Comput..

[6]  Ingo Wegener,et al.  The Analysis of Evolutionary Algorithms on Sorting and Shortest Paths Problems , 2004 .

[7]  Yaonan Wang,et al.  Multi-objective self-adaptive differential evolution with elitist archive and crowding entropy-based diversity measure , 2010, Soft Comput..

[8]  Kalyanmoy Deb,et al.  Reference point based multi-objective optimization using evolutionary algorithms , 2006, GECCO.

[9]  Patrick D. Surry,et al.  The COMOGA Method: Constrained Optimisation by Multi-Objective Genetic Algorithms , 1997 .

[10]  F. Glover,et al.  Handbook of Metaheuristics , 2019, International Series in Operations Research & Management Science.

[11]  Hisao Ishibuchi,et al.  A multi-objective genetic local search algorithm and its application to flowshop scheduling , 1998, IEEE Trans. Syst. Man Cybern. Part C.

[12]  Marc Schoenauer,et al.  Constrained GA Optimization , 1993, ICGA.

[13]  Tapabrata Ray,et al.  An Evolutionary Algorithm for Constrained Optimization , 2000, GECCO.

[14]  Tapabrata Ray,et al.  Infeasibility Driven Evolutionary Algorithm for Constrained Optimization , 2009 .

[15]  Frank Neumann,et al.  On the Effects of Adding Objectives to Plateau Functions , 2009, IEEE Transactions on Evolutionary Computation.

[16]  Hisao Ishibuchi,et al.  Multiobjectivization from two objectives to four objectives in evolutionary multi-objective optimization algorithms , 2010, 2010 Second World Congress on Nature and Biologically Inspired Computing (NaBIC).

[17]  Frank W. Ciarallo,et al.  Helper-objective optimization strategies for the Job-Shop Scheduling Problem , 2011, Appl. Soft Comput..

[18]  Carlos A. Coello Coello,et al.  Use of Multiobjective Optimization Concepts to Handle Constraints in Genetic Algorithms , 2005, Evolutionary Multiobjective Optimization.

[19]  Edwin D. de Jong,et al.  Reducing bloat and promoting diversity using multi-objective methods , 2001 .

[20]  David E. Goldberg,et al.  A niched Pareto genetic algorithm for multiobjective optimization , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[21]  Andrew Philippides,et al.  Multi-objectivization of the Tool Selection Problem on a Budget of Evaluations , 2013, EMO.

[22]  Kalyanmoy Deb,et al.  A Hybrid Evolutionary Multi-objective and SQP Based Procedure for Constrained Optimization , 2007, ISICA.

[23]  Anabela Simões,et al.  Memory-based CHC algorithms for the dynamic traveling salesman problem , 2011, GECCO '11.

[24]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[25]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[26]  Marjan Mernik,et al.  Exploration and exploitation in evolutionary algorithms: A survey , 2013, CSUR.

[27]  Jouni Lampinen,et al.  Constrained Real-Parameter Optimization with Generalized Differential Evolution , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[28]  C. Coello.  TREATING CONSTRAINTS AS OBJECTIVES FOR SINGLE-OBJECTIVE EVOLUTIONARY OPTIMIZATION , 2000 .

[29]  Yuren Zhou,et al.  An orthogonal design based constrained evolutionary optimization algorithm , 2007 .

[30]  Gregorio Toscano Pulido,et al.  Locality-based multiobjectivization for the HP model of protein structure prediction , 2012, GECCO '12.

[31]  Sushil J. Louis,et al.  Pareto OptimalityGA-Easiness and Deception (Extended Abstract) , 1993, International Conference on Genetic Algorithms.

[32]  Edwin D. de Jong,et al.  Multi-objective diversity maintenance , 2006, GECCO '06.

[33]  Henrik Esbensen,et al.  Finding (Near-)Optimal Steiner Trees in Large Graphs , 1995, International Conference on Genetic Algorithms.

[34]  Stéphane Doncieux,et al.  Overcoming the bootstrap problem in evolutionary robotics using behavioral diversity , 2009, 2009 IEEE Congress on Evolutionary Computation.

[35]  Yong Wang,et al.  A Multiobjective Optimization-Based Evolutionary Algorithm for Constrained Optimization , 2006, IEEE Transactions on Evolutionary Computation.

[36]  Kenneth O. Stanley,et al.  Exploiting Open-Endedness to Solve Problems Through the Search for Novelty , 2008, ALIFE.

[37]  Eduardo Segredo,et al.  Parallel island-based multiobjectivised memetic algorithms for a 2D packing problem , 2011, GECCO '11.

[38]  Frank W. Ciarallo,et al.  Multiobjectivization via Helper-Objectives With the Tunable Objectives Problem , 2012, IEEE Transactions on Evolutionary Computation.

[39]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[40]  Hussein A. Abbass,et al.  Searching under Multi-evolutionary Pressures , 2003, EMO.

[41]  M. Jensen.  Helper-Objectives: Using Multi-Objective Evolutionary Algorithms for Single-Objective Optimisation , 2004 .

[42]  R. Storn,et al.  Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .

[43]  David W. Corne,et al.  Quantifying the Effects of Objective Space Dimension in Evolutionary Multiobjective Optimization , 2007, EMO.

[44]  Hisao Ishibuchi,et al.  Incorporation of Scalarizing Fitness Functions into Evolutionary Multiobjective Optimization Algorithms , 2006, PPSN.

[45]  Peter J. Fleming,et al.  Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization , 1993, ICGA.

[46]  Kalyanmoy Deb,et al.  Multiobjective Problem Solving from Nature: From Concepts to Applications , 2008, Natural Computing Series.

[47]  A. Oyama,et al.  NEW CONSTRAINT-HANDLING METHOD FOR MULTI-OBJECTIVE MULTI-CONSTRAINT EVOLUTIONARY OPTIMIZATION AND ITS APPLICATION TO SPACE PLANE DESIGN , 2005 .

[48]  Souma Chowdhury,et al.  Improvements to single-objective constrained predator–prey evolutionary optimization algorithm , 2010 .

[49]  Hussein A. Abbass,et al.  Multiobjective optimization for dynamic environments , 2005, 2005 IEEE Congress on Evolutionary Computation.

[50]  Stéphane Doncieux,et al.  Using behavioral exploration objectives to solve deceptive problems in neuro-evolution , 2009, GECCO.

[51]  Xin Yao,et al.  Performance Scaling of Multi-objective Evolutionary Algorithms , 2003, EMO.

[52]  Wenyin Gong,et al.  A multiobjective differential evolution algorithm for constrained optimization , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[53]  Tapabrata Ray,et al.  Optimum Oil Production Planning Using Infeasibility Driven Evolutionary Algorithm , 2013, Evolutionary Computation.

[54]  Gara Miranda,et al.  Improving the diversity preservation of multi-objective approaches used for single-objective optimization , 2013, 2013 IEEE Congress on Evolutionary Computation.

[55]  Joshua D. Knowles,et al.  Multiobjectivization by Decomposition of Scalar Cost Functions , 2008, PPSN.

[56]  Yuren Zhou,et al.  An Adaptive Tradeoff Model for Constrained Evolutionary Optimization , 2008, IEEE Transactions on Evolutionary Computation.

[57]  David W. Corne,et al.  Properties of an adaptive archiving algorithm for storing nondominated vectors , 2003, IEEE Trans. Evol. Comput..

[58]  David Greiner,et al.  Improving Computational Mechanics Optimum Design Using Helper Objectives: An Application in Frame Bar Structures , 2007, EMO.

[59]  Jean-Baptiste Mouret.  Novelty-Based Multiobjectivization , 2011 .

[60]  Graham Kendall,et al.  Diversity in genetic programming: an analysis of measures and correlation with fitness , 2004, IEEE Transactions on Evolutionary Computation.

[61]  Joshua D. Knowles,et al.  Multiobjective Optimization in Bioinformatics and Computational Biology , 2007, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[62]  Tapabrata Ray,et al.  Performance of infeasibility empowered memetic algorithm for CEC 2010 constrained optimization problems , 2010, IEEE Congress on Evolutionary Computation.

[63]  Samir W. Mahfoud.  Crowding and Preselection Revisited , 1992, PPSN.

[64]  Carlos A. Coello Coello,et al.  Constrained Optimization via Multiobjective Evolutionary Algorithms , 2008, Multiobjective Problem Solving from Nature.

[65]  Stéphane Doncieux,et al.  Encouraging Behavioral Diversity in Evolutionary Robotics: An Empirical Study , 2012, Evolutionary Computation.

[66]  Qingfu Zhang,et al.  Multiobjective evolutionary algorithms: A survey of the state of the art , 2011, Swarm Evol. Comput..

[67]  Efrn Mezura-Montes,et al.  Constraint-Handling in Evolutionary Optimization , 2009 .

[68]  Carlos A. Coello Coello,et al.  Handling constraints using multiobjective optimization concepts , 2004 .

[69]  Gary B. Lamont,et al.  Applications Of Multi-Objective Evolutionary Algorithms , 2004 .

[70]  Ernesto Benini,et al.  Genetic Diversity as an Objective in Multi-Objective Evolutionary Algorithms , 2003, Evolutionary Computation.

[71]  Kazutoshi Sakakibara,et al.  Multi-objective approaches in a single-objective optimization environment , 2005, 2005 IEEE Congress on Evolutionary Computation.

[72]  Kalyanmoy Deb,et al.  An Investigation of Niche and Species Formation in Genetic Function Optimization , 1989, ICGA.

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

[74]  Andres Angantyr,et al.  Constrained optimization based on a multiobjective evolutionary algorithm , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

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

[76]  Gary G. Yen,et al.  A generic framework for constrained optimization using genetic algorithms , 2005, IEEE Transactions on Evolutionary Computation.

[77]  Hisao Ishibuchi,et al.  Evolutionary many-objective optimization: A short review , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[78]  Stéphane Doncieux,et al.  Behavioral diversity measures for Evolutionary Robotics , 2010, IEEE Congress on Evolutionary Computation.

[79]  Eckart Zitzler,et al.  Reducing Bloat in GP with Multiple Objectives , 2008, Multiobjective Problem Solving from Nature.

[80]  C. Coello,et al.  CONSTRAINT-HANDLING USING AN EVOLUTIONARY MULTIOBJECTIVE OPTIMIZATION TECHNIQUE , 2000 .

[81]  Yuren Zhou,et al.  Multi-objective and MGG evolutionary algorithm for constrained optimization , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[82]  Joshua D. Knowles,et al.  Investigations into the Effect of Multiobjectivization in Protein Structure Prediction , 2008, PPSN.

[83]  Pietro Simone Oliveto,et al.  Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods Theoretical Analysis of Diversity Mechanisms for Global Exploration Theoretical Analysis of Diversity Mechanisms for Global Exploration , 2022 .

[84]  Abel García-Nájera,et al.  Preserving population diversity for the multi-objective vehicle routing problem with time windows , 2009, GECCO '09.

[85]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[86]  Eduardo Segredo,et al.  Analysing the Robustness of Multiobjectivisation Approaches Applied to Large Scale Optimisation Problems , 2013, EVOLVE.

[87]  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 .

[88]  Enrique Alba,et al.  Design Issues in a Multiobjective Cellular Genetic Algorithm , 2007, EMO.

[89]  Aimin Zhou,et al.  Dynamic multi-objective differential evolution for solving constrained optimization problem , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[90]  Gunar E. Liepins,et al.  Genetic Algorithms Applications to Set Covering and Traveling Salesman Problems , 1990 .

[91]  Alexandros Agapitos,et al.  An Investigation of Fitness Sharing with Semantic and Syntactic Distance Metrics , 2012, EuroGP.

[92]  Yuping Wang,et al.  Preference Bi-objective Evolutionary Algorithm for Constrained Optimization , 2005, CIS.

[93]  Xavier Blasco Ferragud,et al.  Multiobjective optimization algorithm for solving constrained single objective problems , 2010, IEEE Congress on Evolutionary Computation.

[94]  Yuren Zhou,et al.  Multiobjective Optimization and Hybrid Evolutionary Algorithm to Solve Constrained Optimization Problems , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[95]  Hisao Ishibuchi,et al.  Optimization of Scalarizing Functions Through Evolutionary Multiobjective Optimization , 2007, EMO.

[96]  R. Courant.  Variational methods for the solution of problems of equilibrium and vibrations , 1943 .

[97]  R. Haftka,et al.  Constrained particle swarm optimization using a bi-objective formulation , 2009 .

[98]  Eduardo Segredo,et al.  Scalability and robustness of parallel hyperheuristics applied to a multiobjectivised frequency assignment problem , 2013, Soft Comput..

[99]  Eduardo Segredo,et al.  A multiobjectivised memetic algorithm for the Frequency Assignment Problem , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[100]  Ingo Wegener,et al.  Real royal road functions--where crossover provably is essential , 2001, Discret. Appl. Math..

[101]  Riccardo Poli,et al.  New ideas in optimization , 1999 .

[102]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.

[103]  Richard A. Watson,et al.  Reducing Local Optima in Single-Objective Problems by Multi-objectivization , 2001, EMO.

[104]  Tapabrata Ray,et al.  Society and civilization: An optimization algorithm based on the simulation of social behavior , 2003, IEEE Trans. Evol. Comput..

[105]  Edmund K. Burke,et al.  USING DIVERSITY TO GUIDE THE SEARCH IN MULTI-OBJECTIVE OPTIMIZATION , 2004 .

[106]  Marco Laumanns,et al.  Combining Convergence and Diversity in Evolutionary Multiobjective Optimization , 2002, Evolutionary Computation.