Deterministic Crowding in genetic algorithm to solve a real-scheduling problem: part 1: Theory

• Autores: Mª Elena Pérez Vázquez, Ángel Manuel Gento Municio
• Localización: Cruzando fronteras : tendencias de contabilidad directiva para el siglo XXI: actas VII Congreso Internacional de Costos y II Congreso de la Asociación Española de Contabilidad Directiva., 2001, ISBN 84-7719-952-3, pág. 334
• Idioma: inglés
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• Dialnet Métricas: 1 Cita
• Resumen

  • The aim of this paper is to solve a real scheduling problem of a manufacturing process when we have several objectives and numerous constraints. The factory is dedicated to the manufacturing of pre-stressed concrete sleepers for siding of the new railways. The first objective is the common in all scheduling problems: to maximize the use of the manufacturing line to satisfy the large current demand. The second is due to the characteristics of this real problem: to minimize the change of the moulds. The traditional resolution methods are ineffective due to the large problem complexity. Because of this we will use a powerful and flexible tool to obtain the best solution (the optimal one or close to it): deterministic crowding genetic algorithms.