Evolutionary, constructive and hybrid procedures for the bi-objective set packing problem

The bi-objective set packing problem is a multi-objective combinatorial optimization problem similar to the well-known set covering/partitioning problems. To our knowledge and surprise, this problem has not yet been studied whereas several applications have been reported. Unfortunately, solving the...

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Vydáno v:	European journal of operational research Ročník 204; číslo 2; s. 206 - 217
Hlavní autoři:	Delorme, Xavier, Gandibleux, Xavier, Degoutin, Fabien
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 16.07.2010 Elsevier Elsevier Sequoia S.A
Edice:	European Journal of Operational Research
Témata:	Applied sciences Approximation Computer Science Decision theory. Utility theory Exact sciences and technology Flows in networks. Combinatorial problems Genetic algorithms Heuristic Hybrid method Metaheuristics Multiple objective programming Multiple objective programming Metaheuristics Set packing problem Hybrid method Operational research and scientific management Operational research. Management science Operations Research Optimization algorithms Packing problem Set packing problem Studies Set packing problem Hybrid method Metaheuristics Multiple objective programming Pareto optimum Covering problem Evolutionary algorithm Multiobjective programming Algorithmics Bin packing problem Coverage Hybridization Set partitioning Randomized algorithm Combinatorial optimization Optimal design Genetic algorithm Heuristic method Greedy algorithm Problem solving Set covering Metamodel
ISSN:	0377-2217, 1872-6860
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Abstract	The bi-objective set packing problem is a multi-objective combinatorial optimization problem similar to the well-known set covering/partitioning problems. To our knowledge and surprise, this problem has not yet been studied whereas several applications have been reported. Unfortunately, solving the problem exactly in a reasonable time using a generic solver is only possible for small instances. We designed three alternative procedures for approximating solutions to this problem. The first is derived from the original ‘Strength Pareto Evolutionary Algorithm’, which is a population-based metaheuristic. The second is an adaptation of the ‘Greedy Randomized Adaptative Search Procedure’, which is a constructive metaheuristic. As underlined in the overview of the literature summarized here, almost all the recent, effective procedures designed for approximating optimal solutions to multi-objective combinatorial optimization problems are based on a blend of techniques, called hybrid metaheuristics. Thus, the third alternative, which is the primary subject of this paper, is an original hybridization of the previous two metaheuristics. The algorithmic aspects, which differ from the original definition of these metaheuristics, are described, so that our results can be reproduced. The performance of our procedures is reported and the computational results for 120 numerical instances are discussed.
AbstractList	The bi-objective set packing problem is a multi-objective combinatorial optimization problem similar to the well-known set covering/partitioning problems. To our knowledge and surprise, this problem has not yet been studied whereas several applications have been reported. Unfortunately, solving the problem exactly in a reasonable time using a generic solver is only possible for small instances. We designed three alternative procedures for approximating solutions to this problem. The first is derived from the original 'Strength Pareto Evolutionary Algorithm', which is a population-based metaheuristic. The second is an adaptation of the 'Greedy Randomized Adaptative Search Procedure', which is a constructive metaheuristic. As underlined in the overview of the literature summarized here, almost all the recent, effective procedures designed for approximating optimal solutions to multi-objective combinatorial optimization problems are based on a blend of techniques, called hybrid metaheuristics. Thus, the third alternative, which is the primary subject of this paper, is an original hybridization of the previous two metaheuristics. The algorithmic aspects, which differ from the original definition of these metaheuristics, are described, so that our results can be reproduced. The performance of our procedures is reported and the computational results for 120 numerical instances are discussed. [PUBLICATION ABSTRACT] The bi-objective set packing problem is a multi-objective combinatorial optimization problem similar to the well-known set covering/partitioning problems. To our knowledge and surprise, this problem has not yet been studied whereas several applications have been reported. Unfortunately, solving the problem exactly in a reasonable time using a generic solver is only possible for small instances. We designed three alternative procedures for approximating solutions to this problem. The first is derived from the original ‘Strength Pareto Evolutionary Algorithm', which is a population-based metaheuristic. The second is an adaptation of the ‘Greedy Randomized Adaptative Search Procedure', which is a constructive metaheuristic. As underlined in the overview of the literature summarized here, almost all the recent, effective procedures designed for approximating optimal solutions to multiobjective combinatorial optimization problems are based on a blend of techniques, called hybrid metaheuristics. Thus, the third alternative, which is the primary subject of this paper, is an original hybridization of the previous two metaheuristics. The algorithmic aspects, which differ from the original definition of these metaheuristics, are described, so that our results can be reproduced. The performance of our procedures is reported and the computational results for 120 numerical instances are discussed. The bi-objective set packing problem is a multi-objective combinatorial optimization problem similar to the well-known set covering/partitioning problems. To our knowledge and surprise, this problem has not yet been studied whereas several applications have been reported. Unfortunately, solving the problem exactly in a reasonable time using a generic solver is only possible for small instances. We designed three alternative procedures for approximating solutions to this problem. The first is derived from the original 'Strength Pareto Evolutionary Algorithm', which is a population-based metaheuristic. The second is an adaptation of the 'Greedy Randomized Adaptative Search Procedure', which is a constructive metaheuristic. As underlined in the overview of the literature summarized here, almost all the recent, effective procedures designed for approximating optimal solutions to multi-objective combinatorial optimization problems are based on a blend of techniques, called hybrid metaheuristics. Thus, the third alternative, which is the primary subject of this paper, is an original hybridization of the previous two metaheuristics. The algorithmic aspects, which differ from the original definition of these metaheuristics, are described, so that our results can be reproduced. The performance of our procedures is reported and the computational results for 120 numerical instances are discussed.
Author	Gandibleux, Xavier Delorme, Xavier Degoutin, Fabien
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Keywords	Set packing problem Hybrid method Metaheuristics Multiple objective programming Pareto optimum Covering problem Evolutionary algorithm Multiobjective programming Algorithmics Bin packing problem Coverage Hybridization Set partitioning Randomized algorithm Combinatorial optimization Optimal design Genetic algorithm Heuristic method Greedy algorithm Problem solving Set covering Metamodel
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References	Gandibleux, Mezdaoui, Fréville (bib20) 1997; vol. 55 Przybylski, A., Gandibleux, X., Ehrgott, M., 2004. Seek and cut algorithm computing minimal and maximal complete efficient solution sets for the biobjective assignment problem. In: MOPGP 04: Sixth International Multi-Objective Programming and Goal Programming Conference on New Trends and Applications, Hammamet, Tunisia, April 14–16, 2004. Lusby, R., Larsen, J., Ryan, D., Ehrgott, M., 2006. Routing trains through railway junctions: A new set packing approach. Tech. Rep., IMM Technical Report 2006-21. Zitzler, E., 1999. Evolutionary algorithms for multiobjective optimization: Methods and applications. Ph.D. Thesis, Swiss Federal Institute of Technology (ETH), Zurich, Suisse. Serafini, P., 1992. Simulated annealing for multiobjective optimization problems. In: Proceedings of the 10th International Conference on Multiple Criteria Decision Making, vol. I, Taipei, Taiwan, pp. 87–96. Ehrgott, Gandibleux (bib13) 2008; vol. 11 Jaszkiewicz (bib30) 2004; vol. 535 Malakooti, Wang, Tandler (bib32) 1990; 28 Gandibleux, Morita, Katoh (bib22) 2001; vol. 1993 Fonseca, C., Fleming, P., 1993. Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization. In: Forrest, S. (Ed.), Proceedings of the Fifth International Conference on Genetic Algorithms, San Mateo, California, University of Illinois at Urbana-Champaign. Morgan Kaufman, San Francisco, CA, pp. 416–423. Czyzak, P., Jaszkiewicz, A., 1997. Pareto simulated annealing. In: Fandel, G., Gal, T. (Eds.), Multiple Criteria Decision Making. Proceedings of the XIIth International Conference, Hagen, Germany. Lecture Notes in Economics and Mathematical Systems, vol. 448. pp. 297–307. Degoutin, F., 2002. Problèmes bi-objectifs en optimisation combinatoire et capacité d’infrastructures ferroviaires. Master Thesis, Université de Valenciennes et du Hainaut Cambrésis, Valenciennes, France (in French). Ehrgott, Gandibleux (bib11) 2004; 12 Zhou, Gen (bib48) 1999; 114 Festa, Resende (bib16) 2002 Veldhuizen, D.A.V., 1999. Multiobjective evolutionary algorithms: Classifications, analyses, and new innovations. Ph.D. Thesis, Graduate School of Engineering, Air Force Institute of Technology, Wright-Patterson AFB, OH. Glover, Laguna (bib25) 1997 Zitzler, Thiele (bib51) 1999; 3 Murata, T., Ishibuchi, H., 1995. MOGA: Multi-objective genetic algorithms. In: Proceedings of the Second IEEE International Conference on Evolutionary Computing, pp. 289–294. Resende, Ribeiro (bib39) 2002 Nemhauser, Wolsey (bib36) 1999 Gandibleux, Fréville (bib19) 2000; 6 Ehrgott, Gandibleux (bib12) 2007; 34 Pitsoulis, Resende (bib37) 2002 Abdelaziz, Chaouachi, Krichen (bib1) 1999 Delorme, Gandibleux, Rodriguez (bib9) 2004; 153 Gandibleux, X., Morita, H., Katoh, N., 1998. A genetic algorithm for 0–1 multiobjective knapsack problem. In: International Conference on Nonlinear Analysis and Convex Analysis (NACA98) Proceedings, Niigata, Japan, July 28–31, 1998. Escudero, Landete, Marin (bib14) 2009; 46 Moscato (bib34) 2000 Medaglia, Fang (bib33) 2003; 149 Zitzler, Laumanns, Thiele (bib50) 2002 Alidaee, Kochenberger, Lewis, Lewis, Wang (bib2) 2008; 186 Barichard, V., Hao, J.-K., 2002. Un algorithme hybride pour le problème de sac à dos multi-objectifs. In: Huitièmes Journées Nationales sur la Résolution Pratique de Problèmes NP-Complets JNPC’2002 Proceedings, Nice, France, May 27–29 (in French). Delorme, X., 2003. Modélisation et résolution de problèmes liés à l’exploitation d’infrastructures ferroviaires. Ph.D. Thesis, Université de Valenciennes et du Hainaut Cambrésis, Valenciennes, France (in French). Hansen, M., 1998. Metaheuristics for multiple objective combinatorial optimization. Ph.D. Thesis, Institute of Mathematical Modelling, Technical University of Denmark, Lyngby (Denmark), Report IMM-PHD-1998-45. Delorme, X., Gandibleux, X., Degoutin, F., 2003. Résolution approchée du problème de set packing bi-objectifs. In: Proceedings de l’École d’Automne de Recherche Opérationnelle de Tours (EARO), pp. 74–80 (in French). Sun, M., 1997. Applying tabu search to multiple objective combinatorial optimization problems. In: Proceedings of the 1997 DSI Annual Meeting, vol. 2, San Diego, CA. Decision Sciences Institute, Atlanta, GA, pp. 945–947. Ehrgott, Gandibleux (bib10) 2002; vol. 52 Ulungu, E.L., 1993. Optimisation combinatoire multicritère: Détermination de l’ensemble des solutions efficaces et méthodes interactives. Ph.D. Thesis, Faculté des Sciences, Université de Mons-Hainaut, Mons, Belgique (in French). Visée, Teghem, Pirlot, Ulungu (bib47) 1998; 12 Jaszkiewicz (bib29) 2001; vol. 507 Coello Coello, Aguirre, Zitzler (bib4) 2007; 181 ILOG, 2002. CPLEX 8.0 (user’s manual). Gandibleux, Ehrgott (bib18) 2005; vol. 310 Feo, Resende (bib15) 1989; 8 Ulungu, Teghem, Fortemps (bib45) 1995 Schaffer, J., 1984. Multiple objective optimization with vector evaluated genetic algorithms. Ph.D. Thesis, Vanderbilt University, Nashville, TN, USA. Hansen (bib27) 1979; vol. 177 Gandibleux, Morita, Katoh (bib23) 2004 Rodriguez, Delorme, Gandibleux, Marlière, Bartusiak, Degoutin, Sobieraj (bib40) 2007; 95 Garey, Johnson (bib24) 1979 Glover (10.1016/j.ejor.2009.10.014_bib25) 1997 Gandibleux (10.1016/j.ejor.2009.10.014_bib23) 2004 10.1016/j.ejor.2009.10.014_bib44 Ulungu (10.1016/j.ejor.2009.10.014_bib45) 1995 10.1016/j.ejor.2009.10.014_bib43 10.1016/j.ejor.2009.10.014_bib46 10.1016/j.ejor.2009.10.014_bib49 Gandibleux (10.1016/j.ejor.2009.10.014_bib19) 2000; 6 Medaglia (10.1016/j.ejor.2009.10.014_bib33) 2003; 149 Hansen (10.1016/j.ejor.2009.10.014_bib27) 1979; vol. 177 Abdelaziz (10.1016/j.ejor.2009.10.014_bib1) 1999 Visée (10.1016/j.ejor.2009.10.014_bib47) 1998; 12 Garey (10.1016/j.ejor.2009.10.014_bib24) 1979 Feo (10.1016/j.ejor.2009.10.014_bib15) 1989; 8 Festa (10.1016/j.ejor.2009.10.014_bib16) 2002 10.1016/j.ejor.2009.10.014_bib17 Escudero (10.1016/j.ejor.2009.10.014_bib14) 2009; 46 Zitzler (10.1016/j.ejor.2009.10.014_bib50) 2002 10.1016/j.ejor.2009.10.014_bib31 Resende (10.1016/j.ejor.2009.10.014_bib39) 2002 Ehrgott (10.1016/j.ejor.2009.10.014_bib10) 2002; vol. 52 Alidaee (10.1016/j.ejor.2009.10.014_bib2) 2008; 186 Gandibleux (10.1016/j.ejor.2009.10.014_bib20) 1997; vol. 55 Gandibleux (10.1016/j.ejor.2009.10.014_bib22) 2001; vol. 1993 Pitsoulis (10.1016/j.ejor.2009.10.014_bib37) 2002 Gandibleux (10.1016/j.ejor.2009.10.014_bib18) 2005; vol. 310 Ehrgott (10.1016/j.ejor.2009.10.014_bib11) 2004; 12 10.1016/j.ejor.2009.10.014_bib21 Malakooti (10.1016/j.ejor.2009.10.014_bib32) 1990; 28 Ehrgott (10.1016/j.ejor.2009.10.014_bib13) 2008; vol. 11 10.1016/j.ejor.2009.10.014_bib26 10.1016/j.ejor.2009.10.014_bib28 Rodriguez (10.1016/j.ejor.2009.10.014_bib40) 2007; 95 10.1016/j.ejor.2009.10.014_bib3 10.1016/j.ejor.2009.10.014_bib5 Jaszkiewicz (10.1016/j.ejor.2009.10.014_bib30) 2004; vol. 535 10.1016/j.ejor.2009.10.014_bib6 Delorme (10.1016/j.ejor.2009.10.014_bib9) 2004; 153 Moscato (10.1016/j.ejor.2009.10.014_bib34) 2000 10.1016/j.ejor.2009.10.014_bib7 10.1016/j.ejor.2009.10.014_bib42 10.1016/j.ejor.2009.10.014_bib8 10.1016/j.ejor.2009.10.014_bib41 Zitzler (10.1016/j.ejor.2009.10.014_bib51) 1999; 3 Zhou (10.1016/j.ejor.2009.10.014_bib48) 1999; 114 Nemhauser (10.1016/j.ejor.2009.10.014_bib36) 1999 Coello Coello (10.1016/j.ejor.2009.10.014_bib4) 2007; 181 Jaszkiewicz (10.1016/j.ejor.2009.10.014_bib29) 2001; vol. 507 Ehrgott (10.1016/j.ejor.2009.10.014_bib12) 2007; 34 10.1016/j.ejor.2009.10.014_bib35 10.1016/j.ejor.2009.10.014_bib38
References_xml	– volume: 12 start-page: 1 year: 2004 end-page: 63 ident: bib11 article-title: Approximative solution methods for multiobjective combinatorial optimization publication-title: TOP (Spanish Journal of Operations Research) – volume: 3 start-page: 257 year: 1999 end-page: 271 ident: bib51 article-title: Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach publication-title: IEEE Transactions on Evolutionary Computation – volume: 46 start-page: 649 year: 2009 end-page: 659 ident: bib14 article-title: A branch-and-cut algorithm for the Winner Determination Problem publication-title: Decision Support Systems – volume: 6 start-page: 361 year: 2000 end-page: 383 ident: bib19 article-title: Tabu search based procedure for solving the 0/1 multiobjective knapsack problem: The two objective case publication-title: Journal of Heuristics – reference: Veldhuizen, D.A.V., 1999. Multiobjective evolutionary algorithms: Classifications, analyses, and new innovations. Ph.D. Thesis, Graduate School of Engineering, Air Force Institute of Technology, Wright-Patterson AFB, OH. – volume: vol. 1993 start-page: 429 year: 2001 end-page: 442 ident: bib22 article-title: The supported solutions used as a genetic information in a population heuristic publication-title: Evolutionary Multi-Criterion Optimization – volume: 12 start-page: 139 year: 1998 end-page: 155 ident: bib47 article-title: Two-phases method and branch and bound procedures to solve the bi-objective knapsack problem publication-title: Journal of Global Optimization – reference: Przybylski, A., Gandibleux, X., Ehrgott, M., 2004. Seek and cut algorithm computing minimal and maximal complete efficient solution sets for the biobjective assignment problem. In: MOPGP 04: Sixth International Multi-Objective Programming and Goal Programming Conference on New Trends and Applications, Hammamet, Tunisia, April 14–16, 2004. – reference: ILOG, 2002. CPLEX 8.0 (user’s manual). – reference: Zitzler, E., 1999. Evolutionary algorithms for multiobjective optimization: Methods and applications. Ph.D. Thesis, Swiss Federal Institute of Technology (ETH), Zurich, Suisse. – volume: vol. 507 start-page: 231 year: 2001 end-page: 240 ident: bib29 article-title: Multiple objective genetic local search algorithm publication-title: Multiple Criteria Decision Making in the New Millennium – volume: vol. 177 start-page: 109 year: 1979 end-page: 127 ident: bib27 article-title: Bicriterion path problems publication-title: Multiple Criteria Decision Making Theory and Application – volume: vol. 535 start-page: 65 year: 2004 end-page: 89 ident: bib30 article-title: Evaluation of multiple objective metaheuristics publication-title: Metaheuristics for Multiobjective Optimisation – start-page: 168 year: 2002 end-page: 183 ident: bib37 article-title: Greedy randomized adaptive search procedures publication-title: Handbook of Applied Optimization – volume: vol. 52 start-page: 369 year: 2002 end-page: 444 ident: bib10 article-title: Multiobjective combinatorial optimization publication-title: Multiple Criteria Optimization: State of the Art Annotated Bibliographic Survey, Kluwer’s International Series in Operations Research and Management Science – year: 2002 ident: bib50 article-title: SPEA2: Improving the strength pareto evolutionary algorithm for multiobjective optimization publication-title: Evolutionary Methods for Design, Optimisation, and Control – volume: vol. 11 year: 2008 ident: bib13 article-title: Hybrid metaheuristics for multi-objective combinatorial optimization publication-title: Hybrid Metaheuristics. An Emerging Approach to Optimization – volume: vol. 55 start-page: 291 year: 1997 end-page: 300 ident: bib20 article-title: A tabu search procedure to solve multiobjective combinatorial optimization problems publication-title: Advances in Multiple Objective and Goal Programming – reference: Degoutin, F., 2002. Problèmes bi-objectifs en optimisation combinatoire et capacité d’infrastructures ferroviaires. Master Thesis, Université de Valenciennes et du Hainaut Cambrésis, Valenciennes, France (in French). – volume: vol. 310 start-page: 33 year: 2005 end-page: 46 ident: bib18 article-title: 1984–2004—20 years of multiobjective metaheuristics. But what about the solution of combinatorial problems with multiple objectives? publication-title: Evolutionary Multi-Criterion Optimization – start-page: 219 year: 2002 end-page: 249 ident: bib39 article-title: Greedy randomized adaptive search procedures publication-title: Handbook in Metaheuristics – start-page: 205 year: 1999 end-page: 212 ident: bib1 article-title: A hybrid heuristic for multiobjective knapsack problems publication-title: Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization – volume: 181 start-page: 1617 year: 2007 end-page: 1723 ident: bib4 article-title: Evolutionary multi-objective optimization publication-title: European Journal of Operational Research – year: 1999 ident: bib36 article-title: Integer and Combinatorial Optimization – reference: Hansen, M., 1998. Metaheuristics for multiple objective combinatorial optimization. Ph.D. Thesis, Institute of Mathematical Modelling, Technical University of Denmark, Lyngby (Denmark), Report IMM-PHD-1998-45. – reference: Czyzak, P., Jaszkiewicz, A., 1997. Pareto simulated annealing. In: Fandel, G., Gal, T. (Eds.), Multiple Criteria Decision Making. Proceedings of the XIIth International Conference, Hagen, Germany. Lecture Notes in Economics and Mathematical Systems, vol. 448. pp. 297–307. – reference: Gandibleux, X., Morita, H., Katoh, N., 1998. A genetic algorithm for 0–1 multiobjective knapsack problem. In: International Conference on Nonlinear Analysis and Convex Analysis (NACA98) Proceedings, Niigata, Japan, July 28–31, 1998. – reference: Lusby, R., Larsen, J., Ryan, D., Ehrgott, M., 2006. Routing trains through railway junctions: A new set packing approach. Tech. Rep., IMM Technical Report 2006-21. – reference: Fonseca, C., Fleming, P., 1993. Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization. In: Forrest, S. (Ed.), Proceedings of the Fifth International Conference on Genetic Algorithms, San Mateo, California, University of Illinois at Urbana-Champaign. Morgan Kaufman, San Francisco, CA, pp. 416–423. – year: 1997 ident: bib25 article-title: Tabu Search – reference: Delorme, X., Gandibleux, X., Degoutin, F., 2003. Résolution approchée du problème de set packing bi-objectifs. In: Proceedings de l’École d’Automne de Recherche Opérationnelle de Tours (EARO), pp. 74–80 (in French). – volume: 8 start-page: 67 year: 1989 end-page: 71 ident: bib15 article-title: A probabilistic heuristic for a computationally difficult set covering problem publication-title: Operations Research Letters – start-page: 325 year: 2002 end-page: 367 ident: bib16 article-title: GRASP: An annotated bibliography publication-title: Essays and Surveys on Metaheuristics – volume: 28 start-page: 2373 year: 1990 end-page: 2392 ident: bib32 article-title: A sensor-based accelerated approach for multi-attribute machinability and tool life evaluation publication-title: International Journal of Production Research – volume: 186 start-page: 504 year: 2008 end-page: 512 ident: bib2 article-title: A new approach for modeling and solving set packing problems publication-title: European Journal of Operational Research – start-page: 555 year: 2004 end-page: 579 ident: bib23 article-title: Evolutionary operators based on elite solutions for biobjective combinatorial optimization publication-title: Applications of Multi-Objective Evolutionary Algorithms – reference: Ulungu, E.L., 1993. Optimisation combinatoire multicritère: Détermination de l’ensemble des solutions efficaces et méthodes interactives. Ph.D. Thesis, Faculté des Sciences, Université de Mons-Hainaut, Mons, Belgique (in French). – year: 1979 ident: bib24 article-title: Computers and Intractability: A Guide to the Theory of NP-Completeness – reference: Serafini, P., 1992. Simulated annealing for multiobjective optimization problems. In: Proceedings of the 10th International Conference on Multiple Criteria Decision Making, vol. I, Taipei, Taiwan, pp. 87–96. – start-page: 228 year: 1995 end-page: 238 ident: bib45 article-title: Heuristics for multi-objective combinatorial optimisation problem by simulated annealing publication-title: MCDM: Theory and Applications – volume: 114 start-page: 141 year: 1999 end-page: 152 ident: bib48 article-title: Genetic algorithm approach on multi-criteria minimum spanning tree problem publication-title: European Journal of Operational Research – reference: Delorme, X., 2003. Modélisation et résolution de problèmes liés à l’exploitation d’infrastructures ferroviaires. Ph.D. Thesis, Université de Valenciennes et du Hainaut Cambrésis, Valenciennes, France (in French). – reference: Schaffer, J., 1984. Multiple objective optimization with vector evaluated genetic algorithms. Ph.D. Thesis, Vanderbilt University, Nashville, TN, USA. – reference: Barichard, V., Hao, J.-K., 2002. Un algorithme hybride pour le problème de sac à dos multi-objectifs. In: Huitièmes Journées Nationales sur la Résolution Pratique de Problèmes NP-Complets JNPC’2002 Proceedings, Nice, France, May 27–29 (in French). – reference: Sun, M., 1997. Applying tabu search to multiple objective combinatorial optimization problems. In: Proceedings of the 1997 DSI Annual Meeting, vol. 2, San Diego, CA. Decision Sciences Institute, Atlanta, GA, pp. 945–947. – volume: 34 start-page: 2674 year: 2007 end-page: 2694 ident: bib12 article-title: Bound sets for biobjective combinatorial optimization problems publication-title: Computers and Operations Research – volume: 95 start-page: 129 year: 2007 end-page: 146 ident: bib40 article-title: RECIFE: Models and tools for analyzing rail capacity publication-title: Recherche Transports Sécurité – volume: 149 start-page: 77 year: 2003 end-page: 101 ident: bib33 article-title: A genetic-based framework for solving (multi-criteria) weighted matching problems publication-title: European Journal of Operational Research – year: 2000 ident: bib34 article-title: Memetic algorithms publication-title: Handbook of Applied Optimization – volume: 153 start-page: 564 year: 2004 end-page: 580 ident: bib9 article-title: GRASP for set packing problems publication-title: European Journal of Operational Research – reference: Murata, T., Ishibuchi, H., 1995. MOGA: Multi-objective genetic algorithms. In: Proceedings of the Second IEEE International Conference on Evolutionary Computing, pp. 289–294. – volume: 149 start-page: 77 issue: 1 year: 2003 ident: 10.1016/j.ejor.2009.10.014_bib33 article-title: A genetic-based framework for solving (multi-criteria) weighted matching problems publication-title: European Journal of Operational Research doi: 10.1016/S0377-2217(02)00484-8 – start-page: 325 year: 2002 ident: 10.1016/j.ejor.2009.10.014_bib16 article-title: GRASP: An annotated bibliography – ident: 10.1016/j.ejor.2009.10.014_bib21 – volume: vol. 507 start-page: 231 year: 2001 ident: 10.1016/j.ejor.2009.10.014_bib29 article-title: Multiple objective genetic local search algorithm – ident: 10.1016/j.ejor.2009.10.014_bib44 – ident: 10.1016/j.ejor.2009.10.014_bib5 doi: 10.1007/978-3-642-59132-7_33 – volume: 34 start-page: 2674 issue: 9 year: 2007 ident: 10.1016/j.ejor.2009.10.014_bib12 article-title: Bound sets for biobjective combinatorial optimization problems publication-title: Computers and Operations Research doi: 10.1016/j.cor.2005.10.003 – start-page: 555 year: 2004 ident: 10.1016/j.ejor.2009.10.014_bib23 article-title: Evolutionary operators based on elite solutions for biobjective combinatorial optimization – ident: 10.1016/j.ejor.2009.10.014_bib35 – volume: vol. 11 year: 2008 ident: 10.1016/j.ejor.2009.10.014_bib13 article-title: Hybrid metaheuristics for multi-objective combinatorial optimization – volume: 3 start-page: 257 issue: 4 year: 1999 ident: 10.1016/j.ejor.2009.10.014_bib51 article-title: Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.797969 – ident: 10.1016/j.ejor.2009.10.014_bib7 – ident: 10.1016/j.ejor.2009.10.014_bib31 – start-page: 219 year: 2002 ident: 10.1016/j.ejor.2009.10.014_bib39 article-title: Greedy randomized adaptive search procedures – year: 1999 ident: 10.1016/j.ejor.2009.10.014_bib36 – volume: vol. 1993 start-page: 429 year: 2001 ident: 10.1016/j.ejor.2009.10.014_bib22 article-title: The supported solutions used as a genetic information in a population heuristic – volume: 95 start-page: 129 year: 2007 ident: 10.1016/j.ejor.2009.10.014_bib40 article-title: RECIFE: Models and tools for analyzing rail capacity publication-title: Recherche Transports Sécurité doi: 10.3166/rts.95.129-146 – ident: 10.1016/j.ejor.2009.10.014_bib3 – ident: 10.1016/j.ejor.2009.10.014_bib26 – volume: 153 start-page: 564 issue: 3 year: 2004 ident: 10.1016/j.ejor.2009.10.014_bib9 article-title: GRASP for set packing problems publication-title: European Journal of Operational Research doi: 10.1016/S0377-2217(03)00263-7 – volume: vol. 52 start-page: 369 year: 2002 ident: 10.1016/j.ejor.2009.10.014_bib10 article-title: Multiobjective combinatorial optimization – ident: 10.1016/j.ejor.2009.10.014_bib43 – volume: 28 start-page: 2373 year: 1990 ident: 10.1016/j.ejor.2009.10.014_bib32 article-title: A sensor-based accelerated approach for multi-attribute machinability and tool life evaluation publication-title: International Journal of Production Research doi: 10.1080/00207549008942872 – volume: 181 start-page: 1617 issue: 3 year: 2007 ident: 10.1016/j.ejor.2009.10.014_bib4 article-title: Evolutionary multi-objective optimization publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2006.08.003 – volume: 46 start-page: 649 year: 2009 ident: 10.1016/j.ejor.2009.10.014_bib14 article-title: A branch-and-cut algorithm for the Winner Determination Problem publication-title: Decision Support Systems doi: 10.1016/j.dss.2008.10.009 – volume: 186 start-page: 504 issue: 2 year: 2008 ident: 10.1016/j.ejor.2009.10.014_bib2 article-title: A new approach for modeling and solving set packing problems publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2006.12.068 – year: 1979 ident: 10.1016/j.ejor.2009.10.014_bib24 – volume: vol. 177 start-page: 109 year: 1979 ident: 10.1016/j.ejor.2009.10.014_bib27 article-title: Bicriterion path problems – volume: 114 start-page: 141 issue: 1 year: 1999 ident: 10.1016/j.ejor.2009.10.014_bib48 article-title: Genetic algorithm approach on multi-criteria minimum spanning tree problem publication-title: European Journal of Operational Research doi: 10.1016/S0377-2217(98)00016-2 – year: 2000 ident: 10.1016/j.ejor.2009.10.014_bib34 article-title: Memetic algorithms – ident: 10.1016/j.ejor.2009.10.014_bib46 – ident: 10.1016/j.ejor.2009.10.014_bib42 – ident: 10.1016/j.ejor.2009.10.014_bib6 – start-page: 205 year: 1999 ident: 10.1016/j.ejor.2009.10.014_bib1 article-title: A hybrid heuristic for multiobjective knapsack problems – volume: vol. 310 start-page: 33 year: 2005 ident: 10.1016/j.ejor.2009.10.014_bib18 article-title: 1984–2004—20 years of multiobjective metaheuristics. But what about the solution of combinatorial problems with multiple objectives? – volume: 12 start-page: 1 issue: 1 year: 2004 ident: 10.1016/j.ejor.2009.10.014_bib11 article-title: Approximative solution methods for multiobjective combinatorial optimization publication-title: TOP (Spanish Journal of Operations Research) – volume: vol. 55 start-page: 291 year: 1997 ident: 10.1016/j.ejor.2009.10.014_bib20 article-title: A tabu search procedure to solve multiobjective combinatorial optimization problems – year: 1997 ident: 10.1016/j.ejor.2009.10.014_bib25 – volume: 6 start-page: 361 issue: 3 year: 2000 ident: 10.1016/j.ejor.2009.10.014_bib19 article-title: Tabu search based procedure for solving the 0/1 multiobjective knapsack problem: The two objective case publication-title: Journal of Heuristics doi: 10.1023/A:1009682532542 – start-page: 168 year: 2002 ident: 10.1016/j.ejor.2009.10.014_bib37 article-title: Greedy randomized adaptive search procedures – start-page: 228 year: 1995 ident: 10.1016/j.ejor.2009.10.014_bib45 article-title: Heuristics for multi-objective combinatorial optimisation problem by simulated annealing – volume: 12 start-page: 139 year: 1998 ident: 10.1016/j.ejor.2009.10.014_bib47 article-title: Two-phases method and branch and bound procedures to solve the bi-objective knapsack problem publication-title: Journal of Global Optimization doi: 10.1023/A:1008258310679 – ident: 10.1016/j.ejor.2009.10.014_bib41 – ident: 10.1016/j.ejor.2009.10.014_bib28 – ident: 10.1016/j.ejor.2009.10.014_bib49 – volume: 8 start-page: 67 year: 1989 ident: 10.1016/j.ejor.2009.10.014_bib15 article-title: A probabilistic heuristic for a computationally difficult set covering problem publication-title: Operations Research Letters doi: 10.1016/0167-6377(89)90002-3 – volume: vol. 535 start-page: 65 year: 2004 ident: 10.1016/j.ejor.2009.10.014_bib30 article-title: Evaluation of multiple objective metaheuristics – ident: 10.1016/j.ejor.2009.10.014_bib8 – year: 2002 ident: 10.1016/j.ejor.2009.10.014_bib50 article-title: SPEA2: Improving the strength pareto evolutionary algorithm for multiobjective optimization – ident: 10.1016/j.ejor.2009.10.014_bib17 – ident: 10.1016/j.ejor.2009.10.014_bib38
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Snippet	The bi-objective set packing problem is a multi-objective combinatorial optimization problem similar to the well-known set covering/partitioning problems. To...
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SubjectTerms	Applied sciences Approximation Computer Science Decision theory. Utility theory Exact sciences and technology Flows in networks. Combinatorial problems Genetic algorithms Heuristic Hybrid method Metaheuristics Multiple objective programming Multiple objective programming Metaheuristics Set packing problem Hybrid method Operational research and scientific management Operational research. Management science Operations Research Optimization algorithms Packing problem Set packing problem Studies
Title	Evolutionary, constructive and hybrid procedures for the bi-objective set packing problem
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