A Two-Phase Iterative Mathematical Programming-Based Heuristic for a Flexible Job Shop Scheduling Problem with Transportation

In a flexible job shop problem with transportation (FJSPT), a typical flexible manufacturing system comprises transporters that pick up and deliver jobs for processing at flexible job shops. This problem has grown in importance through the wide use of automated transporters in Industry 4.0. In this...

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Bibliographic Details
Published inApplied sciences Vol. 13; no. 8; p. 5215
Main Authors Lim, Che Han, Moon, Seung Ki
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.04.2023
Subjects
Automation
Benchmarks
Employment
Energy consumption
flexible job shop
Flexible manufacturing systems
Genetic algorithms
Graph representations
Heuristic
Heuristic job shop scheduling
Industry 4.0
Job shop scheduling
job shop scheduling problem with transportation
Job shops
Linear programming
Mathematical programming
mixed integer linear programming
Problem solving
Production engineering
Scheduling
simultaneous scheduling
Solution space
Transportation industry
Iran
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Summary:In a flexible job shop problem with transportation (FJSPT), a typical flexible manufacturing system comprises transporters that pick up and deliver jobs for processing at flexible job shops. This problem has grown in importance through the wide use of automated transporters in Industry 4.0. In this article, a two-phase iterative mathematical programming-based heuristic is proposed to minimize makespan using a machine-operation assignment centric decomposition scheme. The first phase approximates the FJSPT through an augmented flexible job shop scheduling problem (FJSP + T) that reduces the solution space while serving as a heuristic in locating good machine-operation assignments. In the second phase, a job shop scheduling problem with transportation (JSPT) network is constructed from these assignments and solved for the makespan. Compared to prior JSPT implementations, the proposed JSPT model considers job pre-emption, which is instrumental in enabling this FJSPT implementation to outperform certain established benchmarks, confirming the importance of considering job pre-emption. Results indicate that the proposed approach is effective, robust, and competitive.
ISSN:2076-3417
2076-3417
DOI:10.3390/app13085215