Hybrid metaheuristics for multi-objective combinatorial optimization.

Hybrid Metaheuristics for Multi-objective Combinatorial Optimization.

Metaheuristic Optimization for the Design of Automatic Control Laws

Moreover, a heuristic method can be easily adapted or combined with other types of methods.

It was presented by Kennedy and Eberhart in 1995 [30].

The particle swarm optimization algorithm was proposed by Kennedy and Eberhart in 1995 [22].

To address this situation, a mathematical model of the problem was constructed and a new heuristic was developed.

The Greedy Randomized Adaptive Search Procedure (GRASP) algorithm is a metaheuristic introduced by Feo and Resende in 1989.

We then content ourselves with having an approximate solution, obtained by a heuristic or a meta-heuristic.

A multi-objective genetic algorithm termed NSGA-II is employed to generate a set of nondominated solutions.

We then content ourselves with having an approximate solution, obtained by a heuristic or a meta-heuristic.

Combination of a Metaheuristic and a Simulation Model for the Scheduling of Resource-constrained Transport Activities, Virginie André, Nathalie Grangeon and Sylvie Norre.

Evolutionary Metaheuristic Based on Genetic Algorithm: Application to Hybrid Flow Shop Problem with Availability Constraints, Nadia Chaaben, Racem Mellouli and Faouzi Masmoudi.

Owing to the complexity of the problem, we propose a genetic algorithm-based method for solving the problem.

A metaheuristic algorithm was used in hybridization with neural networks, and support vector machine approaches and their