Integrated process planning and scheduling by an agent-based ant colony optimization

Authors:
C. W. Leung;T. N. Wong;K. L. Mak;R. Y. K. Fung
Affiliations:
Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong;Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong;Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong;Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong
Venue:
Computers and Industrial Engineering
Year:
2010

Citing 6
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Abstract

This paper presents an ant colony optimization (ACO) algorithm in an agent-based system to integrate process planning and shopfloor scheduling (IPPS). The search-based algorithm which aims to obtain optimal solutions by an autocatalytic process is incorporated into an established multi-agent system (MAS) platform, with advantages of flexible system architectures and responsive fault tolerance. Artificial ants are implemented as software agents. A graph-based solution method is proposed with the objective of minimizing makespan. Simulation studies have been established to evaluate the performance of the ant approach. The experimental results indicate that the ACO algorithm can effectively solve the IPPS problems and the agent-based implementation can provide a distributive computation of the algorithm.