4.7 Article

Multi-criteria scheduling of realistic flexible job shop: a novel approach for integrating simulation modelling and multi-criteria decision making

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TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2023.2238084

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Partial Flexible Job Shop Scheduling Problem (PFJSSP); Multi-Criteria Decision Making (MCDM); Discrete Event Simulation (DES); Priority Dispatching Rules (PDR); Composite Dispatching Rules (CDR); >

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Increased flexibility in job shops requires shop floor engineers to make more complex decisions. Partial Flexible Job Shop Scheduling (PFJSS) is a subset of job shop problems with practical applications. This study proposes a novel method integrating Multi-Criteria Decision Making (MCDM) methods and Discrete Event Simulation (DES) Model to determine job priorities in large-scale problems.
Increased flexibility in job shops leads to more complexity in decision-making for shop floor engineers. Partial Flexible Job Shop Scheduling (PFJSS) is a subset of Job shop problems and has substantial application in the real world. Priority Dispatching Rules (PDRs) are simple and easy to implement for making quick decisions in real-time. The present study proposes a novel method of integrating Multi-Criteria Decision Making (MCDM) methods and the Discrete Event Simulation (DES) Model to define job priorities in large-scale problems involving multiple criteria. DES approach is employed to model the PFJSS to evaluate Makespan, Flow Time, and Tardiness-based measures considering static and dynamic job arrivals. The proposed approach is implemented in a benchmark problem and large-scale PFJSS. The integration of MCDM methods and simulation models offers the flexibility to choose the parameters that need to govern the ranking of jobs. The solution given by the proposed methods is tested with the best-performing Composite Dispatching Rules (CDR), combining several PDR, which are available in the literature. Proposed MCDM approaches perform well for Makespan, Flow Time, and Tardiness-based measures for large-scale real-world problems. The proposed methodology integrated with the DES model is easy to implement in a real-time shop floor environment.

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