Development and Evaluation of Algorithms for Scheduling Two Unrelated Parallel Processors

Given a group of tasks and two non-identical processors with the ability to complete each task, how should the tasks be assigned to complete the group of tasks as quickly as possible? This thesis considers this unrelated parallel machine scheduling problem with the objective of minimizing the completion time of a group of tasks (the makespan) from the perspective of a local printed circuit board manufacturer. An analytical model representing the job dependent processing time for each manufacturing line is developed and actual job data supplied by the manufacturer is used for analysis. Two versions of a complete enumeration algorithm which identify the optimal assignment schedule are presented. Several classic assignment heuristics are considered with several additional heuristics developed as part of this work. The algorithms are evaluated and their performance compared for jobs built at the local manufacturing site. Finally, a cost-benefit tradeoff for the algorithms considered is presented