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The single-machine early/tardy (E/T) scheduling problem is addressed in this research. The objective of this problem is to minimize the total amount of earliness and tardiness. Earliness and tardiness are weighted equally and the due date is common and large (unrestricted) for all jobs. Machine setup time is included and is considered sequence-dependent.(More)
¾In this paper we propose a tabu search implementation to solve the unrelated parallel machines scheduling problem with sequence-and machine-dependent setup times to minimize the schedule's makespan. The problem is NP-hard and finding an optimal solution efficiently is unlikely. Therefore, heuristic techniques are more appropriate to find near-optimal(More)
Analyzing systems by means of simulation is necessarily a time consuming process. This becomes even more pronounced when models of multiple systems must be compared. In general, and even more so in today's fast-paced environment, competitive pressure does not allow for waiting on the results of a lengthy analysis. That competitive pressure also makes it(More)
This paper addresses the non-preemptive unrelated parallel machine scheduling problem with machine-dependent and job sequence-dependent setup times. All jobs are available at time zero, all times are deterministic, and the objective is to minimize the makespan. This is a NP-hard problem and in this paper, a two-stage ant colony optimization (ACO) algorithm(More)
We summarize our methodology for modeling space shuttle processing using discrete event simulation. Why the project was initiated, what the overall goals were, how it was funded, and who were the members of the project team are identified. We describe the flow of the space shuttle flight hardware through the supporting infrastructure and how the model was(More)
The problem addressed in this paper is scheduling jobs on unrelated parallel machines with sequence-dependent setup times to minimize the maximum completion time (i.e., the makespan). This problem is NP-hard even without including setup times. Adding sequence-dependent setup times adds another dimension of complexity to the problem and obtaining optimal(More)