Research

Job Scheduling with Dual Criteria and Sequence-dependent Setups: Mathematical Versus Genetic Programming

Flexibility, speed, and efficiency are major challenges for operations managers in today's knowledge-intensive organizations. Such requirements are converted into three production scheduling criteria: (a) minimize the impact of setup times in flexible production lines when moving from one product to another, (b) minimize number of tardy jobs, and (c) minimize overall production time, or makespan, for a given set of products or services. There is a wide range of solution methodologies for such NP-hard scheduling problems. While mathematical programming models provide optimal solutions, they become too complex to model for large scheduling problems. Simultaneously, heuristic approaches are simpler and very often independent of the problem size, but provide “good” rather than optimal solutions. This paper proposes and compares two alternative solutions: 0-1 mixed integer linear programming and genetic programming. It also provides guidelines that can be used by practitioners in the process of selecting the appropriate scheduling methodology.

Publication Information
Article Title: Job Scheduling with Dual Criteria and Sequence-dependent Setups: Mathematical Versus Genetic Programming
Journal: Omega (2004)
Vol. 32
Author(s): Lee, Sang M;  Asllani, A
Researcher Information
    
Lee, Sang M
Lee, Sang M
Emeritus
Expertise:
  • Entrepreneurship
  • Information Systems
  • International - Europe
  • International - South and Central America
  • International - Asia
Management
CoB 325 AA
P.O. Box 880491
University of Nebraska-Lincoln
Lincoln, NE 68588-0491, USA
Phone: (402) 472-3915
slee1@unl.edu