An Approach to Develop a Dynamic Job Shop Scheduling by Fuzzy Rule Based System and Comparative Study with the Traditional Priority Rules

Abstract

This paper aims at developing a dynamic job shop scheduling by establishing fuzzy rule based system and comparing its effectiveness with the traditional priority rules. In order to understand the priorities of different jobs in a job shop, the paper investigates all the contributing criteria of different parameters. Since the traditional priority rules only emphasis on a single parameter at a time, the authors propose a method of obtaining a schedule which incorporates all the desired contribution criteria of the parameters used. This method includes establishing a Fuzzy priority rule. Fuzzy is an appropriate model when uncertainty and irregularities are present. It also allows modeling of a significant number of alternatives across different parameters considered in a job shop. Hence, a dynamic job shop schedule can be developed using the established fuzzy priority rule. This research is based on an example of jobs arriving in a regular semi-automated job shop, not a fully automated or software based job shop. The practical implications of this paper is to identify the proper parameters and evaluate their contribution criteria on the required conditions so that managers can determine the proper scheduling and sequence of the jobs to be machined in the job shop. This study provides a deterministic method for local managers to assess the effects of job shop scheduling and sequence of jobs.