Genetic tabu search for the multi-objective knapsack problem

Tsinghua Science and Technology

Volumn 8, Issue 1, 2003, Pages 8-13

  Barichard, Vincent ^a   Hao, Jin Kao ^a  

^a UNIVERSITÉ D'ANGERS   (France)

Author keywords

Genetic tabu search; Hybrid algorithm; Search space

Indexed keywords

BENCHMARKING; CONSTRAINT THEORY; FUNCTIONS; MATHEMATICAL OPERATORS; OPTIMIZATION;

GENETIC TABU SEARCH; HYBRID ALGORITHMS; KNAPSACK PROBLEMS; SEARCH SPACE; TABU SEARCH OPERATORS;

GENETIC ALGORITHMS;

EID: 0038448210     PISSN: 10070214     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (16)

1. Serafini P. Simulated annealing for multiobjective optimization problems. In: Proc. of 10th Int. Conf. on MCDM, 1992, 1: 87-96.
2. Ulungu E L, Teghem J, Fortemps Ph, Tuyttens D. MOSA method: A tool for solving multiobjective combinatorial optimization problems. Journal of Multi-Criteria Decision Analysis, 1999, 8: 221-336.
3. Gandibleux S, Mezdaoui N, Freville A. A multiobjective tabu search procedure to solve combinatorial optimization problems. In: Lecture Notes in Economics and Mathematical Systems. 1997: 291-300.
4. Schaffer J D. Multiple objective optimization with vector evaluated genetic algorithms [Ph. D. Dissertation]. Vanderbilt University, 1984.
5. Srinivas N, Deb K. Multiobjective optimization using non dominated sorting in genetic algorithms. Evolutionary Computation, 1994, 2(3): 221-248.
6. Deb K, Goel T. Controlled elitist non-dominated sorting genetic algorithms for better convergence. In: Proceedings of Evolutionary Multi-Criterion Optimization, 2001: 67-81.
7. Zitzler E, Thiele L. An evolutionary algorithm for multiobjective optimization: The strength Pareto approach. Technical Report 43, 1998.
8. Corne D W, Knowles J D. M-PAES: A memetic algorithm for multi-objective optimization. In: Proceedings of the 2000 Congress on Evolutionary Computation (CEC 2000), 2000.
9. Khor E F, Tan K C, Lee T H. Tabu-based exploratory evolutionary algorithm for effective multi-objective optimization. In: Proceedings of Evolutionary Multi-Criterion Optimization, 2001: 344-358.
10. Jaszkiwicz A. On the performance of multiple objective genetic local search on the 0/1 knapsack problem: A comparative experiment. Research report, Institute of Computing Science, Poznan University of Technology. RA-002, 2000.
11. Galinier P, Hao J K. Hybrid evolutionary algorithms for graph coloring. Journal of Combinatorial Optimization, 1999, 3(4): 379-397.
12. Jaszkiewicz A. Experiments done with the MOMHLib. http://www-ides.cs.put.poznan.pl/jkaszkiewicz/MOMHLib/, 2002.
13. Glover F, Laguna M. Tabu Search. Kluwer Acadmic Publishers, 1997.
14. Zitzler E, Thiele L. Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Transactions on Evolutionary Computation, 1999, 3: 257-271.
15. Zitzler E, Thiele L. Multiobjective optimization using evolutionary algorithms: A comparative case study. Lecture Notes in Computer Science. Springer, 1998: 292-301.
16. Vasquez M, Hao J-K. A hybrid approach for the 0-1 multidimensional knapsack problem. In Proc. of the 13th Int. Joint Conference on Artificial Intelligence (IJCAI-01). 2001, 1: 328-333.