Designing A Model of the Gravity Algorithm and Genetic Algorithm to Solve the Fuzzy Job Shop Machine Scheduling Problem in the Case of Bi-Objectives (Case Study)

Abstract

This study presented an approach and framework for building a hybrid model of the gravity search algorithm and the genetic algorithm, to solve any of the fuzzy workshop scheduling problems (FJSSP) by fuzzing the processing times with a fuzzy number and fuzzing the due date with a fuzzy number. The gravity search algorithm was used to improve the performance of the genetic algorithm from During the generation of an initial generation of size l, representing close-to-optimal solutions, it is used by the genetic algorithm to perform the process of mating, substitution and mutation. The study was applied to Al-Saima Printing and Publishing Co. Ltd., where the fuzzy processing times and fuzzy due dates were recorded for four different works processed by eleven machines according to the nature of the work, and based on historical data in the company’s records. Finally, the study was able to reach a set of conclusions, the most important of which is achieving the research hypothesis, which is that the hybrid model proposed by the researcher is better in obtaining the optimal sequence of actions; To reduce completion time and reach customer satisfaction by delivering the product by the specified due date using the gravity search algorithm fuzzing method and the genetic algorithm fuzzing method.