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The Manpower Allocation Problem With Time Windows And Job-teaming Constraints: A Branch-and-price Approach

机译:有时间窗和工作团队约束的人力分配问题:一种分支定价方法

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In this paper,we consider the manpower allocation problem with time windows,job-teaming constraints and a limited number of teams (m-MAPTWTC).Given a set of teams and a set of tasks,the problem is to assign to each team a sequential order of tasks to maximize the total number of assigned tasks.Both teams and tasks may be restricted by time windows outside which operation is not possible.Some tasks require cooperation between teams,and all teams cooperating must initiate execution simultaneously.We present an integer programming model for the problem,which is decomposed using Dantzig-Wolfe decomposition.The problem is solved by column generation in a branch-and-price framework.Simultaneous execution of tasks is enforced by the branching scheme.To test the efficiency of the proposed algorithm,12 realistic test instances are introduced.The algorithm is able to find the optimal solution in 11 of the test instances.The main contribution of this article is the addition of synchronization between teams in an exact optimization context.
机译:在本文中,我们考虑了具有时间窗,工作团队约束和团队数量有限(m-MAPTWTC)的人力分配问题。给定一组团队和一组任务,问题是为每个团队分配一个任务的顺序顺序以最大化分配的任务总数。两个团队和任务都可能受到无法进行操作的时间窗口的限制。某些任务需要团队之间的合作,并且所有团队合作必须同时启动执行。我们提供一个整数通过Dantzig-Wolfe分解分解该问题的编程模型。在分支价格框架中通过列生成解决该问题。通过分支方案强制执行任务的并行执行。以测试所提算法的效率,介绍了12个实际的测试实例。该算法能够在11个测试实例中找到最佳解决方案。本文的主要贡献是增加了同步投注团队之间在精确的优化环境中。

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