A GENETIC ALGORITHM APPROACH TO SOLVE A FLEXIBLE JOB SHOP PROBLEM WITH DUE DATE

Abstract

Scheduling is one of the most critical elements of any production system as many shop activities are basing on it and the optimization of system performance procedures can be done with proper scheduling of shop floor activities. Flexible Job Shop Scheduling Problem (FJSSP) is a vital scheduling problem which has received substantial significance in the manufacturing area. Flexible Job-shop Scheduling Problem is the extension of Job Shop Scheduling (JSS) which allows an operation to be executed on more than one machine and is also computationally NP-hard. Our study proposes an efficient scheduling method using the genetic algorithm (GA) along with the due date in order to minimize the “make-span time” (Cmax) as it is one of the imperative parameter of such problem. This research will discuss the outcomes of the FT06 problem concerning the makespan. And in the end this dissertation will draw deduction on the basis of this research and will provide some recommendations/proposal as well. The results of the proposed strategy prove it to be a more resourceful technique as compared to the existing methods.