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A greedy heuristic for shift minimization personnel task scheduling problem

机译:轮班最小化人员任务调度问题的贪婪启发式方法

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Shift Minimization Personnel Task Scheduling Problem (SMPTSP) is assigning a given set of predetermined tasks (with known start and finish times) to a minimum number of heterogeneous workers with predetermined shifts. Each task can be performed only by a specific subset of workers. Every task must be assigned to a worker. A worker cannot perform more than one task at a time, and tasks cannot be preempted. SMPTSP is NP-hard, but there is practical interest in solving very large instances of it in ground crew scheduling of a large airline in a large airport. Recently, there have been a few papers reporting various solution methods for large instances of SMPTSP. However, solving very large instances of SMPTSP remains a challenge. In this paper, we propose a novel greedy heuristic solution method for SMPTSP. A reduced problem is solved iteratively by selecting the best possible assignment of tasks to one worker. We have tested the Greedy heuristic method on 3 sets of available large test problems. The results show that the heuristic method performs well relative to the current solution methods, and has the added advantage of being able to solve very large instances fast. (C) 2018 Elsevier Ltd. All rights reserved.
机译:班次最小化人员任务计划问题(SMPTSP)将给定的一组预定任务(具有已知的开始和完成时间)分配给最少数量的具有预定班次的异构工人。每个任务只能由特定的工人子集执行。必须将每个任务分配给工人。工人一次不能执行多个任务,因此不能抢占任务。 SMPTSP很难满足NP的要求,但是在大型机场的大型航空公司的地勤人员调度中,解决它的大量实例确实引起了人们的实际兴趣。最近,有几篇论文报告了针对SMPTSP大型实例的各种解决方法。但是,解决SMPTSP的大量实例仍然是一个挑战。在本文中,我们提出了一种新颖的贪婪启发式求解方法。通过为一个工人选择最佳的任务分配,可以迭代地解决减少的问题。我们已经在3组可用的大型测试问题上测试了Greedy启发式方法。结果表明,启发式方法相对于当前的求解方法表现良好,并且具有能够快速求解非常大的实例的附加优点。 (C)2018 Elsevier Ltd.保留所有权利。

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