A graph-based constraint programming approach for the integrated process planning and scheduling problem. (July 2021)

• Record Type: Journal Article
• Authors: Zhang, Luping; Yu, Chunxia; Wong, T.N.
• Is Part Of: Computers & operations research. Volume 131(2021)
• Publication Date: 2021-07
• Subjects: Integrated process planning and scheduling -- Constraint programming -- CP Optimizer -- Graph-based modelling -- AND/OR graph; Operations research -- Periodicals; Electronic digital computers -- Periodicals; 004.05
• DOI: 10.1016/j.cor.2021.105282
• Languages: English
• ISSNs: 0305-0548

Abstract

Highlights: The integrated process planning and scheduling (IPPS) problem is solved. AND/OR graphs are tailored to cope with IPPS representation. A graph-based constraint programming model is proposed. Benchmark tests revealed outstanding performance of the proposed approach. Abstract: Integration of process planning and scheduling (IPPS) is to carry out both functions simultaneously. This paper provides a graph-based constraint programming (GCP) approach to solve the type-2 IPPS problem that takes AND/OR graphs as input. The proposed GCP approach is implemented based on the IBM ILOG CP Optimizer. AND/OR graph is tailored to cope with IPPS instances. Directed arcs define both precedence and presence relationships. The or-link, a set of mutually-exclusive operations, is defined to represent alternative process routes. Interval variables and scheduling-oriented constraints are adopted to project the IPPS-specific AND/OR graph to a concise CP model with which minimizing makespan is incorporated as the objective. The GCP approach is tested on a set of benchmark problems. Experimental results show that the proposed approach outperforms compared algorithms on major IPPS instances.