Computational Study on Job Flow Shop Scheduling Using MiniMax Optimizing Algorithm

Shop scheduling is a critical part of manufacturing systems. The goal is to find an efficient schedule that optimizes system performance. Finding a feasible schedule becomes more difficult as the number of jobs and machines increases. The present research aims to study the computational study of different optimization methods to solve job flow shop scheduling problems. This paper reviews computational research of varying optimization methods to solve job flow shop scheduling problems. We discuss Johnson's algorithm, Campbell, Dudek, and Smith's (CDS) Approach, and Gantt chart and propose a Minimax optimization. This new method has the least processing time in the machine in the current situation. We present substantial computational results using MiniMax optimization techniques. From the result, we can conclude that the proposed algorithm gives less processing time and more frequently an optimal schedule than the other studied methods.