Titlebook: Hybrid Metaheuristics; Third International Francisco Almeida,María J. Blesa Aguilera,Michael Conference proceedings 2006 Springer-Verlag

Senescent

A Multi-population Parallel Genetic Algorithm for Highly Constrained Continuous Galvanizing Line Scegarded as the most difficult process among the finishing lines due to its multi-objective and highly-constrained nature. In this paper, we present a multi-population parallel genetic algorithm (MPGA) with a new genetic representation called . . nearest neighbor representation, and with a new commun

揉雜

Improvement in the Performance of Island Based Genetic Algorithms Through Path Relinking,ome individuals. This way, several zones of the landscape are explored in parallel and solutions with different features can be discovered. The interchange of information is a key point for the performance of these algorithms, since the combination of those solutions usually produces better ones. In

Pulmonary-Veins

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WAX

Multi-level Ant Colony Optimization for DNA Sequencing by Hybridization,ization has attracted quite a lot of interest in the optimization community. This led to the development of several metaheuristic approaches such as tabu search and evolutionary algorithms. In this work we propose an ant colony algorithm to resolve this problem. In addition, we apply our algorithm w

aptitude

Hybrid Approaches for Rostering: A Case Study in the Integration of Constraint Programming and Loca paper we investigate two of them, namely the employment of local search to improve a solution found by constraint programming and the exploitation of a constraint model to perform the exploration of the local neighborhood. We apply the two approaches to a real-world personnel rostering problem aris

arbovirus

A Reactive Greedy Randomized Variable Neighborhood Tabu Search for the Vehicle Routing Problem with of designing least cost routes from a depot to geographically dispersed customers. The routes must be designed such that each customer is visited only once by exactly one vehicle without violating capacity and time window constraints. The proposed solution method is a multi-start local search appro

orthodox

Incorporating Inference into Evolutionary Algorithms for Max-CSP, an evolutionary algorithm for search assisted by an inference algorithm, the variable elimination procedure. The hybrid algorithm obtained is adapted in such way that a balance between exploitation and exploration is preserved. The results are presented for the Max-CSP optimization task.

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