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Article Dans Une Revue Computers and Operations Research Année : 2020

Lower and upper bounds for the non-linear generalized assignment problem

Résumé

We consider a non-linear version of the Generalized Assignment Problem, a well-known strongly N P-hard combinatorial optimization problem. We assume that the variables are continuous and that objective function and constraints are defined by non-linear functions of the variables. A mathematical model is introduced and used to derive upper bounds on the optimal solution value. We present constructive heuristics, obtained from decomposition and non-linear programming tools, and a binary linear programming model that provides approximate solutions. By combining the various methods and a local search framework, we finally obtain a hybrid heuristic approach. Extensive computational experiments show that the proposed methods outperform the direct application of non-linear solvers and provide high quality solutions in a reasonable amount of time.
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hal-03008701 , version 1 (16-11-2020)

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  • HAL Id : hal-03008701 , version 1

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Claudia d'Ambrosio, Silvano Martello, Michele Monaci. Lower and upper bounds for the non-linear generalized assignment problem. Computers and Operations Research, 2020. ⟨hal-03008701⟩
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