A PSO‐based procedure for a bi‐level multi‐objective TOC‐based job‐shop scheduling problem

This study presents an application of particle swarm optimisation (PSO) algorithm for a bi‐level multi‐objective job‐shop scheduling problem. The bi‐level decision‐making requirement stems from the concept of theory of constraints. At the first level, the decision is made by concentrating on minimising idle time on the system bottleneck. The second‐level decision is made to plan other machines while maintaining the maximum use of the bottleneck and gaining improvements in other performance measures. This paper proposed a PSO‐based procedure for solving the bi‐level programming problem. The proposed procedure simplifies the solution method by simultaneously providing solutions for the objective of both levels. In addition, during the schedule generation process, the job‐shop case applied in this study also considers the machine set‐up time, transfer lot size and product demands to make the model more realistic. The numerical examples are given to demonstrate how this approach works. The results from this procedure are compared with the solutions obtained by a commercial optimiser, the LINGO 10 software package. This proposed PSO is implemented in C# programming language in order to obtain the final solution within the short computational time.