Resumen

HERRERA FRANKLIN, Jorge  y  ROSETE, Alejandro. Multiobjective approach for the fuzzy variable cost and size bin packing problem. Rev cuba cienc informat [online]. 2021, vol.15, n.2, pp. 44-61.  Epub 01-Jun-2021. ISSN 2227-1899.

The research addresses a fuzzy variant of the Variable Cost and Size Bin Packing Problem where an overload of the bins is allowed. The level of overload is defined by alpha-cuts or membership values which generates crisp instances that conform the fuzzy problem. The empirical sampling of the alpha-cuts has the problem that every single crisp instance must be solved as well as it can be missed interesting solutions that improve the trade-off between cost and capacity. In the present work a proposal is introduced where the problem of obtaining the fuzzy solution is treated as a multiobjective problem aiming to minimize the cost while maximizing the membership value of the solution. For this, the multiobjective metaheuristics Local Search, Ulungu Simulated Annealing, Genetic Algorithm and its variant NSGA-II were used. Several operators based on the First Fit Decreasing heuristic were implemented. The experimental results showed that the NSGA-II turns out to be the most efficient and at the same time the slowest, but without becoming unfeasible its use in large instances. It was also verified in a group of fuzzy instances, of which the exact solution is known for 11 membership values, that this method allows obtaining solutions that improve membership values with the same cost.

Palabras clave : multiobjective optimization; fuzzy variable cost and size bin packing problem; metaheuristics; parametric approach.

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