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Communication Dans Un Congrès Année : 2005

Cooperating Memetic and Branch-and-Cut Algorithms for Solving the Multidimensional Knapsack Problem

Résumé

Recent work in combinatorial optimization indicates the high potential of combining metaheuristics with integer linear programming (ILP) techniques. We study here a hybrid system in which a memetic algorithm (MA) and a general purpose ILP solver based on branch-and-cut (B&C) are executed in parallel and continuously exchange information in a bidirectional, asynchronous way. As target problem, we consider the multidimensional knapsack problem (MKP). The memetic algorithm uses a direct binary encoding of candidate solutions and repair and local improvement strategies that are steered by pseudo-utility ratios. As B&C framework we use the general purpose commercial ILP-solver CPLEX. The information exchanged between the two heterogenous algorithms are so-far best primal solutions and promising dual variable values of solutions to certain linear programming (LP) relaxations. These dual variable values are used in the MA to update the pseudo-utility ratios of local improvement and repair.
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Dates et versions

hal-01317132 , version 1 (31-05-2016)

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  • HAL Id : hal-01317132 , version 1

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Jakob Puchinger, Martin Gruber, Günther R. Raidl. Cooperating Memetic and Branch-and-Cut Algorithms for Solving the Multidimensional Knapsack Problem. 6th Metaheuristics International Conference (MIC 2005), Aug 2005, Vienna, Austria. ⟨hal-01317132⟩

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