Metaheuristics and cooperative approaches for the Bi-objective Ring Star Problem

Computers and Operations Research

Volumn 37, Issue 6, 2010, Pages 1033-1044

  Liefooghe, A ^a   Jourdan, L ^a   Talbi, E G ^a  

^a ECOLE CENTRALE DE LILLE   (France)

Author keywords

Cooperative approach; Metaheuristic; Multi objective optimization; Ring star problem

Indexed keywords

BENCHMARK TESTS; COOPERATIVE STRATEGY; HYBRID APPROACH; LOCAL SEARCH; META HEURISTICS; METAHEURISTIC; MULTI-OBJECTIVE METAHEURISTICS; NON-HYBRID ALGORITHMS; ROUTING PROBLEMS; SEARCH METHOD; STAND -ALONE; STATE-OF-THE-ART METHODS;

EVOLUTIONARY ALGORITHMS; HEURISTIC METHODS;

MULTIOBJECTIVE OPTIMIZATION;

EID: 71749109584     PISSN: 03050548     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cor.2009.09.004     Document Type: Article

References (48)

1. Labbé M., Laporte G., Rodríguez Martín I., and Salazar González J.J. The ring star problem: polyhedral analysis and exact algorithm. Networks 43 (2004) 177-189
2. Labbé M., Laporte G., Rodríguez Martín I., and Salazar González J.J. Locating median cycles in networks. European Journal of Operational Research 160 2 (2005) 457-470
3. Jozefowiez N., Semet F., and Talbi E.-G. Multi-objective vehicle routing problems. European Journal of Operational Research 189 2 (2008) 293-309
4. Liefooghe A, Jourdan L, Basseur M, Talbi E-G, Burke EK. Metaheuristics for the bi-objective ring star problem. In: Eighth European conference on evolutionary computation in combinatorial optimisation (EvoCOP 2008). Lecture notes in computer science, vol. 4472. Napoli, Italy: Springer; 2008. p. 206-17.
5. Basseur M., and Burke E.K. Indicator-based multi-objective local search. IEEE congress on evolutionary computation (CEC 2007) (2007), IEEE Press, Singapore 3100-3107
6. Zitzler E, Künzli S. Indicator-based selection in multiobjective search. In: Eighth international conference on parallel problem solving from nature (PPSN VIII). Lecture notes in computer science, vol. 3242. Birmingham, UK: Springer; 2004. p. 832-42.
7. Deb K., Agrawal S., Pratap A., and Meyarivan T. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6 2 (2002) 182-197
8. Coello Coello C.A., Van Veldhuizen D.A., and Lamont G.B. Evolutionary algorithms for solving multi-objective problems (2002), Kluwer Academic Publishers, Boston, MA, USA
9. Deb K. Multi-objective optimization using evolutionary algorithms (2001), Wiley, Chichester, UK
10. Ehrgott M., and Gandibleux X. Approximative solution methods for multiobjective combinatorial optimization. Top 12 1 (2004) 1-89
11. Labbé M., Laporte G., and Rodríguez Martín I. Path, tree and cycle location. In: Crainic T., and Laporte G. (Eds). Fleet management and logistics (1998), Kluwer Academic Publishers, Boston, MA, USA 187-204
12. Labbé M, Laporte G, Rodríguez Martín I, Salazar González JJ. The median cycle problem. Working paper, CRT-99-29, Université de Montréal, 1999.
13. Miettinen K. Nonlinear multiobjective optimization vol. 12 (1999), Kluwer Academic Publishers, Boston, MA, USA
14. Moreno Pérez J.A., Moreno-Vega J.M., and Rodríguez Martín I. Variable neighborhood tabu search and its application to the median cycle problem. European Journal of Operations Research 151 2 (2003) 365-378
15. Renaud J., Boctor F.F., and Laporte G. Efficient heuristics for median cycle problems. Journal of the Operational Research Society 55 2 (2004) 179-186
16. Dias TCS, de Sousa Filho GF, Macambira EM, Cabral LAF, Fampa MHC. An efficient heuristic for the ring star problem. In: Fifth international workshop on experimental algorithms (WEA 2006), Lecture notes in computer science, vol. 4007. Menorca, Spain: Springer; 2006. p. 24-35.
17. Current J.R., and Schilling D.A. The median tour and maximal covering tour problems: formulations and heuristics. European Journal of Operational Research 73 (1994) 114-126
18. Doerner K., Focke A., and Gutjahr W.J. Multicriteria tour planning for mobile healthcare facilities in a developing country. European Journal of Operational Research 179 3 (2007) 1078-1096
19. Beasley J.E., and Nascimento E.M. The vehicle routing-allocation problem: a unifying framework. Top 4 1 (1996) 65-86
20. Schaffer JD. Multiple objective optimization with vector evaluated genetic algorithms. In: First international conference on genetic algorithms (ICGA 1985), Pittsburgh, PA, USA: Lawrence Erlbaum Associates; 1985. p. 93-100.
21. Fonseca CM, Fleming PJ. Genetic algorithms for multiobjective optimization: formulation, discussion and generalization. In: Fifth international conference on genetic algorithms (ICGA 1993). Urbana-Champaign, IL, USA: Morgan Kaufmann; 1993. p. 416-23.
22. Xu J., Chiu S.Y., and Glover F. Optimizing a ring-based private line telecommunication network using tabu search. Management Science 45 3 (1999) 330-345
23. Baldacci R., Dell'Amico M., and Salazar Gonzàlez J.J. The capacitated m-ring star problem. Operations Research 55 6 (2007) 1147-1162
24. Labbé M., and Laporte G. Maximizing user convenience and postal service efficiency in post box location. Belgian Journal of Operations Research Statistics and Computer Science 26 (1986) 21-35
25. Akinc U., and Srikanth K. Optimal routing and process scheduling for a mobile service facility. Networks 22 2 (1992) 163-183
26. Burke EK, Kendall G., editors. Search methodologies: introductory tutorials in optimization and decision support techniques. Berlin, Germany: Springer; 2005.
27. In: Glover F.W., and Kochenberger G.A. (Eds). Handbook of metaheuristics of international series in operations research management science vol. 57 (2003), Kluwer Academic Publishers, Boston, MA, USA
28. Paquete L., and Stützle T. Stochastic local search algorithms for multiobjective combinatorial optimization: a review. In: Gonzalez T.F. (Ed). Handbook of approximation algorithms and metaheuristics of computer & information science series vol. 13 (2007), Chapman & Hall, CRC, London
29. Zitzler E., Thiele L., Laumanns M., Foneseca C.M., and Grunert da Fonseca V. Performance assessment of multiobjective optimizers: an analysis and review. IEEE Transactions on Evolutionary Computation 7 2 (2003) 117-132
30. Helbig S., and Pateva D. On several concepts for ε{lunate}- efficiency. OR Spektrum 16 3 (1994) 179-186
31. Hernández-Díaz A.G., Santana-Quintero L.V., Coello C.A.C., and Molina J. Pareto-adaptive epsilon-dominance. Evolutionary Computation 15 4 (2007) 493-517
32. Lourenco H.R., Martin O., and Stützle T. Iterated local search. In: Glover F., and Kochenberger G. (Eds). Handbook of metaheuristics of international series in operations research & management science vol. 57 (2002), Kluwer Academic Publishers, Norwell, MA, USA 321-353 [Chapter 11]
33. Zitzler E., and Thiele L. Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach. IEEE Transactions on Evolutionary Computation 3 4 (1999) 257-271
34. Laumanns M, Zitzler E, Thiele L. On the effects of archiving, elitism, and density based selection in evolutionary multi-objective optimization. In: First international conference on evolutionary multi-criterion optimization (EMO 2001), Lecture notes in computer science, vol. 1993. Zurich, Switzerland: Springer; 2001. p. 181-96.
35. Corne DW, Knowles JD, Oates MJ. The pareto envelope-based selection algorithm for multiobjective optimization. In: Sixth international conference on parallel problem solving from nature (PPSN VI), Lecture notes in computer science, vol. 1917. Paris, France: Springer; 2000. p. 839-48.
36. Valenzuela C.L. A simple evolutionary algorithm for multi-objective optimization (SEAMO). IEEE congress on evolutionary computation (CEC 2002) (2002), IEEE Press, Piscataway, NJ, USA 717-722
37. Knowles J., and Corne D. Bounded Pareto archiving: theory and practice. In: Gandibleux X., Sevaux M., Sörensen K., and T'Kindt V. (Eds). Metaheuristics for multiobjective optimisation of lecture notes in economics and mathematical systems vol. 535 (2004), Springer, Berlin 39-64 [Chapter 2]
38. Bean J. Genetic algorithms and random keys for sequencing and optimization. ORSA Journal on Computing 6 2 (1994) 154-160
39. Liefooghe A, Jourdan L, Talbi E-G. A unified model for evolutionary multiobjective optimization and its implementation in a general purpose software framework: ParadisEO-MOEO. Research Report RR-6906, Institut National de Recherche en Informatique et Automatique (INRIA); 2009.
40. Reinelt G. TSPLIB-a traveling salesman problem library. ORSA Journal on Computing 3 4 (1991) 376-384
41. Knowles J, Thiele L, Zitzler E. A tutorial on the performance assessment of stochastic multiobjective optimizers. Technical Report, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, Switzerland; 2006 [revised version].
42. Bleuler S, Laumanns M, Thiele L, Zitzler E. PISA-a platform and programming language independent interface for search algorithms. In: Second international conference on evolutionary multi-criterion optimization (EMO 2003), Lecture notes in computer science, vol. 2632. Faro, Portugal: Springer; 2003. p. 494-508.
43. Liefooghe A, Jourdan L, Talbi E-G. Metaheuristics and their hybridization to solve the bi-objective ring star problem: a comparative study. Research Report RR-6515, Institut National de Recherche en Informatique et Automatique (INRIA); 2008.
44. Talbi E.-G. A taxonomy of hybrid metaheuristics. Journal of Heuristics 8 2 (2002) 541-564
45. Ehrgott M., and Gandibleux X. Hybrid metaheuristics for multi-objective combinatorial optimization. In: Blum C., Blesa M.J., Roli A., and Sampels M. (Eds). Hybrid metaheuristics-an emergent approach for optimization of studies in computational intelligence vol. 114 (2008), Springer, Berlin, Germany 221-259 [Chapter 9]
46. Meunier H., Talbi E.-G., and Reininger P. A multiobjective genetic algorithm for radio network optimization. IEEE congress on evolutionary computation (CEC 2000) (2000), IEEE Press, San Diego, USA 317-324
47. Ishibuchi H., Yoshida T., and Murata T. Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling. IEEE Transactions on Evolutionary Computation 7 2 (2003) 204-223
48. Basseur M., Seynhaeve F., and Talbi E.-G. Design of multi-objective evolutionary algorithms: application to the flow shop scheduling problem. IEEE congress on evolutionary computation (2002), IEEE Press, Piscataway, NJ, USA 1151-1156