Original scientific paper

https://doi.org/10.17559/TV-20151121212910

Integrated process planning and scheduling using genetic algorithms

Imran Ali Chaudhry orcid.org/0000-0001-6726-0753 ; Department of Industrial Engineering, College of Engineering, University of Hail, Ha’il, Saudi Arabia
Muhammad Usman orcid.org/0000-0003-4596-0550 ; Department of Industrial Engineering, College of Engineering, University of Hail, Ha’il, Saudi Arabia

Abstract

Process planning and scheduling are two of the most important functions in any manufacturing system. Traditionally process planning and scheduling are considered as two separate functions. In this paper a Genetic Algorithm (GA) for integrated process planning and scheduling is proposed where selection of the best process plan and scheduling of jobs in a job shop environment are done simultaneously. In the proposed approach a domain independent spreadsheet based approach is presented to solve this class of problems. The precedence relations among job operations are considered in the model, based on which implicit representation of a feasible process plans for each job can be done. To verify the performance and feasibility of the presented approach, the proposed algorithm has been evaluated against a number of benchmark problems that have been adapted from the previously published literature. The experimental results show that the proposed approach can efficiently achieve optimal or near-optimal solutions for the problems adopted from literature. It is also demonstrated that the proposed algorithm is of general purpose in application and could be used for the optimisation of any objective function without changing the model or the basic GA routine.

Keywords

integrated process planning and scheduling (IPPS); genetic algorithms; job shop

Hrčak ID:

188236

URI

https://hrcak.srce.hr/188236

Publication date:

25.10.2017.

Article data in other languages: croatian

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