WORKER SCHEDULING OF BANBURY PROCESS USING GOAL PROGRAMMING: A TIRE MANUFACTURING COMPANY CAES STUDY

Authors

  • Srisawat Supsomboon The Sirindhorn International Thai – German Graduate School of Engineering (TGGS), King Mongkut’s University of Technology North Bangkok (KMUTNB), Bangkok, Thailand
  • Chonnipa Chaihanit The Sirindhorn International Thai – German Graduate School of Engineering (TGGS), King Mongkut’s University of Technology North Bangkok (KMUTNB), Bangkok, Thailand
  • Anan Butrat The Sirindhorn International Thai – German Graduate School of Engineering (TGGS), King Mongkut’s University of Technology North Bangkok (KMUTNB), Bangkok, Thailand

DOI:

https://doi.org/10.23055/ijietap.2024.31.2.9717

Keywords:

Worker Scheduling, Shift Scheduling, Goal Programming Method, Mathematical model, Integer Linear Programming

Abstract

In today’s competitive business landscape, organizations must streamline their planning and management processes for efficiency and profitability. Effective resource management, especially in the case of human resources, is crucial. Scheduling challenges in human resource management become more complex when considering worker skills. Balancing fairness for workers and the company necessitates the inclusion of additional constraints and variables, making manual problem-solving more time-consuming and complex. This study proposes a Goal Programming Method, a mathematical model that addresses both primary and goal constraints, to optimize solutions and minimize deviation variables. The case study of a real manufacturer’s Banbury process department with 51 workers, 24 tasks, and two shifts has been analyzed. The mathematical model is utilized to allocate tasks, optimize worker skill utilization, and identify positions to close when worker availability falls short.

Published

2024-04-18

How to Cite

Supsomboon, S., Chaihanit, C., & Butrat, A. (2024). WORKER SCHEDULING OF BANBURY PROCESS USING GOAL PROGRAMMING: A TIRE MANUFACTURING COMPANY CAES STUDY . International Journal of Industrial Engineering: Theory, Applications and Practice, 31(2). https://doi.org/10.23055/ijietap.2024.31.2.9717

Issue

Section

Production Planning and Control