A MIXED-INTEGER PROGRAMMING MODEL FOR THE JOB SCHEDULING PROBLEM IN A PRODUCTION COMPANY

Abstract

Purpose: In this study, a mixed-integer programming model is developed to minimize the total lateness and total completion time of the jobs in an automotive company. In order to respond rapidly to the continuous customer demand through the production, the work schedule of engineers in the research and development department is considered flexibly. Methodology: In the study, the mixed-integer programming model is supported by the analytical hierarchy process model to determine the weighted values of total tardiness and total completion times. The developed model is applied to the automotive company using the real data and the problem is solved using the GAMS CPLEX 24.1.3 software. Findings: In this job scheduling problem, the total completion time is decreased to 622 hours from 10149 hours, maximum tardiness is decreased to 9 hours from 104 hours and total tardiness is decreased to 13 hours from 860 hours by using the proposed model. Originality: The proposed model is used for the job scheduling purpose in compliance with the structure of the automotive industry company using the machine scheduling modeling principles and Analytical Hierarchy Process together. Keywords: Parallel Machine Scheduling, Optimization, Mixed Integer Programming, Analytical Hierarchical Process.