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Vehicle Routing Problem (VRP) is a widely known NP-Hard combinatorial optimization problem. This paper presents a proposal of a memetic algorithm (MA) with simulated annealing (SA) as trajectory-based method for solving the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). A novel crossover operator, the Single Breaking-point Sequence Based Crossover (SBSBX), is introduced and compared...
Born primarily as means to model knowledge, ontologies have successfully been exploited to enable knowledge exchange among people, organizations and software agents. However, because of strong subjectivity of ontology modeling, a matching process is necessary in order to lead ontologies into mutual agreement and obtain the relative alignment, i.e., the set of correspondences among them. The aim of...
Time and space assembly line balancing considers realistic multiobjective versions of the classical assembly line balancing industrial problems, involving the joint optimization of conflicting criteria such as the cycle time, the number of stations, and/or the area of these stations. The aim of this contribution is to present a new multiobjective memetic algorithm based on ant colony optimization...
Memetic algorithms are effective algorithms to obtain reliable and accurate solutions for complex continuous optimization problems. Nowadays, high dimensional optimization problems are an interesting field of research. The high dimensionality introduces new problems for the optimization process, requiring more scalable algorithms that, at the same time, could explore better the higher domain space...
In this work we present a simple way to introduce gradient-based information as a means to improve the search performed by a multi-objective evolutionary algorithm (MOEA). Our proposal can be easily incorporated into any MOEA, and is able to improve its performance when solving continuous bi-objective problems. We propose a novel mechanism to control the balance between the local search, and the global...
Real life optimization problems often involve one or more constraints, and there is a significant interest among the research community to develop efficient algorithms to solve such constrained optimization problems. This paper presents a memetic algorithm combining the strengths of an evolutionary algorithm and a local search strategy. Since solutions of constrained optimization problems are expected...
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