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MEMOTS: a memetic algorithm integrating tabu search for combinatorial multiobjective optimization

Thibaut Lust, Jacques Teghem (2008)

RAIRO - Operations Research

We present in this paper a new multiobjective memetic algorithm scheme called MEMOX. In current multiobjective memetic algorithms, the parents used for recombination are randomly selected. We improve this approach by using a dynamic hypergrid which allows to select a parent located in a region of minimal density. The second parent selected is a solution close, in the objective space, to the first parent. A local search is then applied to the offspring. We experiment this scheme with a new multiobjective...

Metaheuristics based on Bin Packing for the line balancing problem

Michel Gourgand, Nathalie Grangeon, Sylvie Norre (2007)

RAIRO - Operations Research

The line balancing problem consits in assigning tasks to stations in order to respect precedence constraints and cycle time constraints. In this paper, the cycle time is fixed and the objective is to minimize the number of stations. We propose to use metaheuristics based on simulated annealing by exploiting the link between the line balancing problem and the bin packing problem. The principle of the method lies in the combination between a metaheuristic and a bin packing heuristic. Two representations of...

MIP-based heuristics for multi-item capacitated lot-sizing problem with setup times and shortage costs

Nabil Absi, Safia Kedad-Sidhoum (2007)

RAIRO - Operations Research

We address a multi-item capacitated lot-sizing problem with setup times that arises in real-world production planning contexts. Demand cannot be backlogged, but can be totally or partially lost. Safety stock is an objective to reach rather than an industrial constraint to respect. The problem is NP-hard. We propose mixed integer programming heuristics based on a planning horizon decomposition strategy to find a feasible solution. The planning horizon is partitioned into several sub-horizons over...

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