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A starting-time-based approach to production scheduling with Particle Swarm Optimization

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4 Author(s)
Grobler, J. ; Ind. Eng., Pretoria Univ. ; Engelbrecht, A.P. ; Joubert, J.W. ; Kok, S.

This paper provides a generic formulation for the complex scheduling problems of Optimatix, a South African company specializing in supply chain optimization. To address the complex requirements of the proposed problem, various additional constraints were added to the classical job shop scheduling problem. These include production downtime, scheduled maintenance, machine breakdowns, sequence-dependent set-up times, release dates and multiple predecessors per job. Differentiation between primary resources (machines) and auxiliary resources (labour, tools and jigs) were also achieved. Furthermore, this paper applies particle swarm optimization (PSO), a stochastic population based optimization technique originating from the study of social behavior of birds and fish, to the proposed problem. Apart from the significance of the paper in that the proposed problem has not been addressed before, the benefit of an improved production schedule can be generalized to include cost reduction, customer satisfaction, improved profitability and overall competitive advantage

Published in:

Computational Intelligence in Scheduling, 2007. SCIS '07. IEEE Symposium on

Date of Conference:

1-5 April 2007

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