Hybrid Population-Based Algorithms for the Bi-Objective Quadratic Assignment Problem

Hybrid Population-Based Algorithms for the Bi-Objective Quadratic Assignment Problem

We present variants of an ant colony optimization (MO-ACO) algorithm and of an evolutionary algorithm (SPEA2) for tackling multi-objective combinatorial optimization problems, hybridized with an iterative improvement algorithm and the Robust Tabu Search algorithm. The performance of the resulting hybrid stochastic local search (SLS) algorithms is experimentally investigated for the bi-objective...

ACO Algorithms for the Quadratic Assignment Problem

A Hybrid Metaheuristic for the Quadratic Assignment Problem

A Hybrid Genetic Algorithm for the Quadratic Assignment Problem

A heuristic technique that combines a genetic algorithm with a Tabu Search algorithm is applied to the Quadratic Assignment Problem (QAP). The hybrid algorithm improves the results obtained through the application of each of these algorithms separately. The QAP is a NP-hard problem and instances of size n > 15 are still considered intractable. The results of our experiments suggest that CHC com...

The bi-objective quadratic multiple knapsack problem: Model and heuristics

The single objective quadratic multiple knapsack problem (QMKP) is a useful model to formulate a number of practical problems. However, it is not suitable for situations where more than one objective needs to be considered. In this paper, we extend the single objective QMKP to the bi-objective case such that we simultaneously maximize the total profit of the items packed into the knapsacks and ...