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Genetic Algorithms for the Resource-Constrained Project Scheduling Problem

Javier Alcaraz Soria
Centro de Investigación Operativa, Departamento de Estadística, Matemáticas e Informática.
Universidad Miguel Hernández de Elche
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Concepción Maroto Álvarez
Departamento de Estadística e Investigación Operativa Aplicadas y Calidad.
Universidad Politécnica de Valencia
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  • Abstract
    Genetic Algorithms have been applied to many diferent optimization problems and they are one of the most promising metaheuristics. In the last years we have focused our work developing efficient genetic algorithms to solve the Resource-Constrained Project Scheduling Problem. We have proposed several algorithms to solve diferent versions of the problem, designing new representations for the solutions, different crossover techniques, innovative mutation mechanisms, efficient local search procedures and other features that will be summarized in this work.
  • Keywords: Project Scheduling, Genetic Algorithms, Metaheuristics, Resource Allocation.
  • AMS Subject classifications: 90B35, 90B99, 90-08.
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