On Space Resource Constrained Job Scheduling Problems- A Container Loading Heuristic Approach

A job scheduling problem is one of the most complicated and well-known combinatorial optimization problems. A previous space resource constrained job scheduling problem stated that the assembly process of a machine requires a certain amount of space on the shop floor within the factory for a period of time. The sizes of the shop floor and machines will determine the number of machines which can be assembled at the same time. There are a few research papers investigating space resource constrained job scheduling problems. In this study, we intend to find a schedule in order to minimize the makespan by converting the container loading problem heuristic into one that solves the space scheduling optimization problem. The processing time requirement for each job is the depth for each box in Pisinger's CLP heuristic. The testing data was obtained from the OR-Library and collected from a real company in central Taiwan during 2008. After validation, we find that our approach is more efficient than other well-known dispatching rules for obtaining the best schedule within the minimum makespan. We also verify that if a job completes early and moves into an unlimited buffer situation, it will generate the less makespan and maybe improve space utilization. We suggest that job height could be included into this problem in future studies.