Tire mixing process scheduling using particle swarm optimization

doi:10.1016/j.cie.2017.06.012

2017-08-01

PRE

DOI：10.1016/j.cie.2017.06.012

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摘要

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The tire manufacturing process consists of four major steps, including mixing, component preparation, building, and curing. Among these, the mixing process is the most important, since it produces a type of synthesized rubber called a compound, which determines various features of the tire and consumes 70% of the overall manufacturing budget. However, despite the importance of mixing, there is little research on this process. Thus, in this study, we consider a scheduling problem for a tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm for minimizing makespan. Specifically, we design a system in which particle coordination and velocity are used to generate a processing sequence for compounds and machine allocation information, while being updated in successive steps. The superiority of the proposed PSO algorithm is shown with numerical experiments that compare the solutions found by the proposed algorithm with those obtained from a mixed integer linear programming model developed in previous research. (C) 2017 Elsevier Ltd. All rights reserved.

Keyword:

Tire mixing process

Compound

Makespan

Sequence-dependent setup time

Flexible job shop scheduling problem

Particle swarm optimization, particle encoding scheme

Error rate