Development and analysis of priority decision rules using MCDM approach for a flexible job shop scheduling: A simulation study

Abstract

Flexible job shop scheduling problem (FJSSP) is a critical operational planning step in manufacturing that ensures on-time delivery of goods leading to customer satisfaction. The process of assigning jobs to machines has a larger solution space and consumes a huge amount of time and effort. This research focuses on solving FJSSP using the discrete event simulation (DES) model and integrates it with Composite Dispatching Rules (CDRs) and multi-criteria decision making (MCDMs) based priority rules. Performance evaluation of the flexible job shop is carried out to minimize the Makespan, mean Flow-Time, mean Tardiness, and maximum Tardiness. Best performing CDRs and hybrid MCDM techniques are employed for minimizing the objectives considered in this study. The proposed solution framework integrates Fuzzy Analytic Hierarchy Process (FAHP) for assigning weights to the criteria and MCDM approaches namely technique for order of preference by similarity to ideal solution (TOPSIS), The Evaluation based on Distance from Average Solution (EDAS), Compromise Programming (CP), and Weighted Average Method (WAM) separately to prioritize the jobs. Benchmark problems of different sizes are tested using the best performing CDRs available in the literature and proposed MCDM approaches. The proposed approach is implemented in a real-world large-scale flexible job shop (FJS) that produces auto components handling 114 job variants with 245 operations using 28 machines. The performance analysis indicates that no single rule outperforms all the objective measures considered in this study. The MCDMs based rules perform better compared to CDRs for large-scale problems by considering realistic criteria such as demand, due date, setup time, process time, customer priority, and number of operations. The methodology proposed in this study can be tailored in terms of the criteria used for ranking and production parameters to be executable for any real-time instance.