Title

Fuzzy cell genetic algorithm approach for flexible flow-line scheduling model

Document Type

Conference Proceeding

Date of Original Version

2-9-2017

Abstract

This paper focuses on makespan minimization for the flow line scheduling problem using a Fuzzy Cell Genetic Algorithm (FCGA). Real world applications of this problem are commonly found in printing and electronic circuit board manufacturing industries. A generalized integer programming (IP) model for this problem is proposed. The Fuzzy Cell Genetic Algorithm (FCGA) is proposed to solve the IP model, which has been proven to be NP-hard. Sample problems are generated with known good solutions to evaluate the effectiveness of the FCGA approach. The FCGA matches the performance of the IP model for small sized problem instances and it is proven to be effective for larger problem instances.

Publication Title

2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016

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