MOTGA: A multiobjective Tchebycheff based genetic algorithm for the multidimensional knapsack problem
This paper presents a new multiobjective genetic algorithm based on the Tchebycheff scalarizing function, which aims to generate a good approximation of the nondominated solution set of the multiobjective problem. The algorithm performs several stages, each one intended for searching potentially non...
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| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2007
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| Texto completo: | http://hdl.handle.net/10316/5482 |
| País: | Portugal |
| Oai: | oai:estudogeral.sib.uc.pt:10316/5482 |
| Resumo: | This paper presents a new multiobjective genetic algorithm based on the Tchebycheff scalarizing function, which aims to generate a good approximation of the nondominated solution set of the multiobjective problem. The algorithm performs several stages, each one intended for searching potentially nondominated solutions in a different part of the Pareto front. Pre-defined weight vectors act as pivots to define the weighted-Tchebycheff scalarizing functions used in each stage. Therefore, each stage focuses the search on a specific region, leading to an iterative approximation of the entire nondominated set. |
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