A Comparative Study of Multiple-Objective Metaheuristics on the Bi-Objective Set Covering Problem and the Pareto Memetic Algorithm
The paper describes a comparative study of multiple-objective metaheuristics on the bi-objective set covering problem. Ten representative methods based on genetic algorithms, multiple start local search, hybrid genetic algorithms and simulated annealing are evaluated in the computational experiment....
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| Vydané v: | Annals of operations research Ročník 131; číslo 1-4; s. 135 - 158 |
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| Médium: | Journal Article |
| Jazyk: | English |
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New York
Springer Nature B.V
01.10.2004
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| ISSN: | 0254-5330, 1572-9338 |
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| Abstract | The paper describes a comparative study of multiple-objective metaheuristics on the bi-objective set covering problem. Ten representative methods based on genetic algorithms, multiple start local search, hybrid genetic algorithms and simulated annealing are evaluated in the computational experiment. Nine of the methods are well known from the literature. The paper introduces also a new hybrid genetic algorithm called Pareto memetic algorithm. The results of the experiment indicate very good performance of hybrid genetic algorithms, however, no algorithm was able to outperform all other methods on all instances. Furthermore, the results indicate that the performance of multiple-objective metaheuristics may differ radically even if the methods are based on the same single objective algorithm and use exactly the same problem-specific operators.[PUBLICATION ABSTRACT] |
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| AbstractList | The paper describes a comparative study of multiple-objective metaheuristics on the bi-objective set covering problem. Ten representative methods based on genetic algorithms, multiple start local search, hybrid genetic algorithms and simulated annealing are evaluated in the computational experiment. Nine of the methods are well known from the literature. The paper introduces also a new hybrid genetic algorithm called Pareto memetic algorithm. The results of the experiment indicate very good performance of hybrid genetic algorithms, however, no algorithm was able to outperform all other methods on all instances. Furthermore, the results indicate that the performance of multiple-objective metaheuristics may differ radically even if the methods are based on the same single objective algorithm and use exactly the same problem-specific operators.[PUBLICATION ABSTRACT] |
| Author | Jaszkiewicz, Andrzej |
| Author_xml | – sequence: 1 givenname: Andrzej surname: Jaszkiewicz fullname: Jaszkiewicz, Andrzej |
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| Cites_doi | 10.1016/S0377-2217(01)00104-7 10.1016/0191-2607(88)90022-2 10.1002/(SICI)1099-1360(199907)8:4<221::AID-MCDA247>3.0.CO;2-O 10.1007/978-3-642-58409-1_17 10.1023/A:1009682532542 10.1007/978-3-642-85970-0_5 10.1016/0377-2217(95)00159-X 10.1109/5326.704576 10.1023/A:1009823419804 10.1162/evco.1994.2.3.221 10.1016/0966-8349(95)00008-6 10.1109/4235.797969 10.1109/TEVC.2002.802873 10.1002/(SICI)1099-1360(199801)7:1<34::AID-MCDA161>3.0.CO;2-6 10.1109/ICEC.1997.592288 10.1016/S0377-2217(96)00023-9 |
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| References | 5276963_CR19 A. Jaszkiewicz (5276963_CR11) 1993 5276963_CR16 E. Marchiori (5276963_CR18) 2000; 1083 D.A. Van Veldhuizen (5276963_CR27) 1999 J.E. Beasly (5276963_CR1) 1996; 94 A. Jaszkiewicz (5276963_CR13) 2002; 137 A. Jaszkiewicz (5276963_CR10) 2001; 26 N. Srinivas (5276963_CR23) 1994; 2 H.R. Lourenço (5276963_CR17) 2001 B.M. Smith (5276963_CR22) 1988; 22A H. Ishibuchi (5276963_CR9) 1998; 28 K. Deb (5276963_CR3) 1993 E. Zitzler (5276963_CR28) 1999; 3 X. Gandibleux (5276963_CR5) 2000; 6 M. Sakawa (5276963_CR20) 1997; 97 P. Serafini (5276963_CR21) 1992; 1 5276963_CR4 A. Jaszkiewicz (5276963_CR14) 2002; 6 5276963_CR8 A. Jaszkiewicz (5276963_CR12) 2001 P. Czy?zak (5276963_CR2) 1998; 7 P. Galinier (5276963_CR7) 1999; 3 R.E. Steuer (5276963_CR24) 1986 É.D. Taillard (5276963_CR25) 1995; 3 M.R. Garey (5276963_CR6) 1979 J.D. Knowles (5276963_CR15) 2000 E.L. Ulungu (5276963_CR26) 1999; 8 |
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| SubjectTerms | Algorithms Experiments Genetic algorithms Heuristic Operations research Optimization Pareto optimum Studies |
| Title | A Comparative Study of Multiple-Objective Metaheuristics on the Bi-Objective Set Covering Problem and the Pareto Memetic Algorithm |
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