Genetic Algorithms for Integrated Optimisation of Precedence-Constrained Production Sequencing and Scheduling

Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 130)

Abstract

This chapter presents the development of genetic algorithms (GA) for integrated optimisation of precedence-constrained production sequencing and scheduling in a multi-production line environment. This class of problem is NP-hard, combinatorial problem, requiring a triple optimisation at the same time: allocation of resources to each production line, production line sequencing and production line scheduling. Due to nature of constraints, the length of solution for the problem is variable. To cope with this variability and search for a global optimum, new strategies for resource allocation, encoding chromosome, crossover and mutation are developed herein. Robustness of the proposed GA is demonstrated by a complex and realistic case study.

Keywords

Income Expense Production Line 

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Copyright information

© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  1. 1.School of Advanced Manufacturing and Mechanical EngineeringUniversity of South AustraliaMawson LakesAustralia

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