Hugo Alfonso

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This work is focussed on the development and analysis of a new class of algorithms, called cellular memetic algorithms (cMAs), which will be evaluated here on the satisfiability problem (SAT). For describing a cMA, we study the effects of adding specific knowledge of the problem to the fitness function, the crossover and mutation operators, and to the local(More)
General cutting problems are concerned with finding the best allocation of a number of items in larger containing regions. These problems can be encountered in numerous areas such as computer science, industrial engineering, logistics, manufacturing, among others. They belong to the family of NP-complete problems. For cases of high complexity deterministic(More)
Over the past few years, a continually increasing number of research efforts have investigated the application of evolutionary computation techniques for the solution of scheduling problems. Scheduling can pose extremely complex combinatorial optimization problems, which belong to the NP-hard family. Last enhancements on evolutionary algorithms include new(More)
Considering the population size is a critical parameter to define in evolutionary computation, in this paper an improved parallel evolutionary algorithm that incorporates different mechanisms to adapt the population size to the current status, is presented. Those mechanisms are based on resizing on fitness improvement GA (PRoFIGA) and variable population(More)
Cellular genetic algorithms (cGAs) are mainly characterized by their spatially decentralized population, in which individuals can only interact with their neighbors. In this work, we study the behavior of a large number of different cGAs when solving the well-known 3-SAT problem. These cellular algorithms differ in the policy of individuals update and the(More)
The Vehicle Routing Problem (VRP) deals with the assignment of a set of transportation orders to a fleet of vehicles and the sequencing of stops for each vehicle to minimize transportation costs. This paper presents two different genetic algorithm models (panmitic and cellular models) for providing solutions for the Capacitated VRP (CVRP), which is mainly(More)
The Vehicle Routing Problem (VRP) deals with the assignment of a set of transportation orders to a fleet of vehicles, and the sequencing of stops for each vehicle to minimize transportation costs. In this paper we study the Capacitated VRP (CVRP), which is mainly characterized by using vehicles of the same capacity. Taking a basic GA to solve the CVRP, we(More)
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