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

TL;DR

This paper introduces a novel integrated approach combining Multi-Criteria Decision Making and Discrete Event Simulation to optimize flexible job shop scheduling, effectively handling complex, large-scale real-world problems with multiple performance criteria.

Contribution

It develops a new method that integrates MCDM and DES models for flexible job shop scheduling, enhancing decision-making flexibility and real-time applicability.

Findings

Proposed approach performs well on large-scale real-world problems.

Integration of MCDM and simulation offers flexible parameter selection.

Method is easy to implement in real-time shop floor environments.

Abstract

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.