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Mixed Integer Programming with Decomposition to Solve a Workforce Scheduling and Routing Problem

机译:混合整数编程用分解来解决员工调度和路由问题

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We propose an approach based on mixed integer programming (MIP) with decomposition to solve a workforce scheduling and routing problem, in which a set of workers should be assigned to tasks that are distributed across different geographical locations. This problem arises from a number of home care planning scenarios in the UK, faced by our industrial partner. We present a mixed integer programming model that incorporates important real-world features of the problem such as defined geographical regions and flexibility in the workers' availability. Given the size of the real-world instances, we propose to decompose the problem based on geographical areas. We show that the quality of the overall solution is affected by the ordering in which the sub-problems are tackled. Hence, we investigate different ordering strategies to solve the sub-problems and show that such decomposition approach is a very promising technique to produce high-quality solutions in practical computational times using an exact optimization method.
机译:我们提出了一种基于混合整数编程(MIP)的方法,分解求解劳动力调度和路由问题,其中应该将一组工人分配给分布在不同地理位置的任务。这个问题来自英国的许多家庭护理计划情景,面向我们的工业伴侣。我们介绍了一个混合整数编程模型,其中包含了重要的实际特征,如确定的地理区域和工人可用性的灵活性。鉴于现实世界的规模,我们建议根据地理区域分解问题。我们表明整个解决方案的质量受到亚问题所在的排序的影响。因此,我们调查了不同的排序策略来解决子问题,并表明这种分解方法是一种使用精确的优化方法在实际计算时间中产生高质量解决方案的非常有希望的技术。

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