A GRASP algorithm for the multi-objective knapsack problem

Proceedings - International Conference of the Chilean Computer Science Society, SCCC

Volumn , Issue , 2004, Pages 69-75

  Vianna, Dalessandro Scares ^a   Arroyo, José Elias Claudio ^a  

^a UCAM Campos   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER HARDWARE; COMPUTER SOFTWARE; DECISION THEORY; FUNCTIONS; HEURISTIC METHODS; LARGE SCALE SYSTEMS; OPTIMIZATION; PARETO PRINCIPLE; PROBLEM SOLVING;

COMBINATORIAL OPTIMIZATION PROBLEMS; GREEDY RANDOMIZED ADAPTIVE SEARCH PROCEDURE (GRASP); KNAPSACK PROBLEMS (KP); MULTI-OBJECTIVE COMBINATORIAL OPTIMIZATION (MOCO);

GENETIC ALGORITHMS;

EID: 21644489834     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. Ben, A.F., Chaouachi, J., and Krichen, S. (1999). "A hybrid heuristic for multiobjective knapsack problems". Em S. Voss, S. Martello, I. Osmaa and C. Roucairol (eds.), Metaheuristics: Advances and trends in local search paradigms for optimization. Dordrecht: Kluwer, 205-212.
2. Coello, C.A.C. (2000). "An updated survey of GA-based multiobjective optimization techniques". ACM Computing Surveys 32(2), 109-143.
3. Czyzak, P., and Jaszkiewicz, A. (1998). "Pareto simulated annealing - a metaheuristic technique for multiple objective combinatorial optimization". Journal of Multi-Criteria Decision Analysis 7, 34-47.
4. Ehrgott, M., and Gandibleux, X. (2000). "A survey and annotated bibliography of multiobjective combinatorial optimization". OR Spektrum 22, 425-460.
5. Feo, T.A., and Resende, M.G.C. (1995). "Greedy randomized adaptive search procedures". Journal of Global Optimization 6, 109-133.
6. Festa P., and Resende M.G.C. (2004). "An annotated bibliography of GRASP'. Relatório técnico. Submitted for the European Journal of Operational Research.
7. Gandibleux, X., and Fréville, A. (2000). "Tabu search based procedure for solving the 0-1 multiobjective knapsack problem: The two objectives case". Journal of Heuristics 6, 361-383.
8. Hansen, P. (1997). 'Tabu search for multiobjective optimization: MOTS". Relatório Técnico. Technical University of Denmark. Paper presented at The 13th International Conference on Multiple Criteria Decision Making. Cape Town, South Africa.
9. Jaskiewicz, A. (2002). "On the performance of multiple objective genetic local search on the 0/1 knapsack problem: A comparative experiment". IEEE Transaction on Evolutionary Computation 6(4), 402-412.
10. Jones, D.F., Mirrazavi, S.K., and Tamiz, M. (2002). "Multi-objective metaheuristics: An overview of the current state-of-art". European Journal of Operational Research 137, 1-19.
11. Murata T., Ishibuchi H., and Gen M. (2001). "Specification of genetic Search directions in cellular multi-objective genetic algorithms". In Zitzler E., Deb K., Thiele L., Coello C.A.C. and Corne D. (eds.), Evolutionary Multi-Criterion optimization, First International Conference, EMO. Lecture Notes in Computer Science. Zurich: Springer, Vol 1, 82-95.
12. Teghem, J., Tuyttens, D., and Ulungu, E.L. (2000). "An iteractive heuristic method for multi-objective combinatorial optimization". Computer and Operations Research 27, 621-634.
13. Ulungu, E.L., and Teghem, J. (1995). "The two phases method: An efficient procedure to solve bi-objective combinatorial optimization problems". Foundations of Computing and Decision Sciences 20 (2), 149-165.
14. Ulungu, E.L., Teghem, J., and Ost, C. (1998). "Efficiency of interactive multi-objective simulated annealing through a case study". Journal of the Operational Research Society 49, 1044-1050.
15. Van Veldhuizen, D.A., and Lamont, G.B. (2000). "Multiobjective evolutionary algorithms: Analyzing the state-of art". Evolutionary Computation 8(2), 125-147.
16. Visée M., Teghem J., Pirlot M., and Ulungu E.L. (1998). "Two-Phases Method and Branch and Bound Procedures to solve the Bi-objectives knapsack Problem". Journal of Global Optimization 12, 139-155.
17. Zitzler, E., and Thiele, L. (1999). "Multiobjective evolutionary algorithms: A comparative case study and the strength pareto approach". IEEE Transactions on Evolutionary Computation 3(4), 257-271.
18. Zitzler, E., Laumanns M., and Thiele L. (2002). "SPEA2: Improving the Strength Pareto Evolutionary Algorithm". In EUROGEN 2001, Evolutionary Methods for Design, Optimization and Control with Applications to Industrial Problems. Vol. 1, Athens, Greece, 95-100.