MOSA method: a tool for solving multiobjective combinatorial optimization problems
✍ Scribed by E.L. Ulungu; J. Teghem; P.H. Fortemps; D. Tuyttens
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 189 KB
- Volume
- 8
- Category
- Article
- ISSN
- 1057-9214
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✦ Synopsis
The success of modern heuristics (Simulated Annealing (S.A.), Tabu Search, Genetic Algorithms, . . . ) in solving classical combinatorial optimization problems has drawn the attention of the research community in multicriteria methods.
In fact, for large-scale problems, the simultaneous difficulties of NP-hard complexity and of multiobjective framework make most Multiobjective Combinatorial Optimization (MOCO) problems intractable for exact methods.
This paper develops the so-called MOSA (Multiobjective Simulated Annealing) method to approximate the set of efficient solutions of a MOCO problem. Different options for the implementation are illustrated and extensive experiments prove the efficiency of the approach. Its results are compared to exact methods on bi-objective knapsack problems.