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GIUSEPPE AIELLO

An integrated approach for modelling and solving multimode job shop scheduling problem using multi objective genetic algorithm

  • Authors: La Scalia, G.; Micale, R.; Aiello, G.; Enea, M.
  • Publication year: 2015
  • Type: Articolo in rivista (Articolo in rivista)
  • OA Link: http://hdl.handle.net/10447/191430

Abstract

In this paper, we present a Multi Objective Genetic Algorithm (MOGA) for modelling and solving the Multimode Job-shop Scheduling Problem (MJSP), which aims at finding the start times and execution modes for the operations of different jobs that optimize a given set of objective functions while verifying precedence and resource constraints. The proposed model can be used to generate alternative schedules based on the relative magnitude and importance of different objectives. Its main contributions are the mode assignment procedure in the chromosome generation and the use of three fitness functions. Its performance is demonstrated by computational results obtained on a set of standard instances and against the best currently available algorithms.