Scheduling and routing models for food rescue and delivery operations
Scheduling and routing models for food rescue and delivery operations
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DOI：
10.1016/j.seps.2017.06.003
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发表时间：
2018-09-01
影响因子：
6.1
通讯作者：
Dixit, V. V.
中科院分区：
文献类型：
--
作者：
Nair, D. J.;Grzybowska, H.;Dixit, V. V.
粮食救援组织是一个非营利组织，通过从不同的粮食供应商那里拯救剩余的粮食，并重新分配给支持不同形式粮食救济的福利机构，帮助缓解饥饿。在这项研究中，我们提出了一个调度和路由模型，旨在同时选择每个食品供应商和福利机构的访问组合，并设计路线，以满足他们所需的服务水平，最大限度地减少总运输成本，同时满足一定的业务约束。这个问题是由悉尼的粮食救济行动造成的。我们的具体目标是开发一个集成的线性规划模型，并提出一个基于禁忌搜索的启发式解决方案的方法，这个调度和路由问题。我们还实现了一个现实的食品救援和交付网络在悉尼的算法。我们测试我们的启发式算法从文献中的实例和小的实例产生类似的Cordeau的基准实例，并验证我们的解决方案的方法对最佳解决方案，通过精确的方法之前，实现它的食品救援和交付网络。计算实验表明，所提出的方法优于现有的算法，并能够解决现实世界的情况下，使用显着更少的资源比在实践中使用。(C)2017爱思唯尔有限公司版权所有
Food rescue organizations are not-for-profit organizations that aid in alleviating hunger, by rescuing the surplus food from different food providers and re-distributing to welfare agencies supporting different forms of food relief. In this study, we present a scheduling and routing model that aims at simultaneously selecting a visit combination for each food provider and welfare agency, and designing routes to meet their required service levels minimizing the total transportation cost, while satisfying certain operational constraints. This problem is driven by food relief operations in Sydney. Our specific goals are to develop an integrated linear programming model and to propose a Tabu Search based heuristic solution approach for this scheduling and routing problem. We also implement the algorithm in a realistic food rescue and delivery network in Sydney. We test our heuristic algorithm on instances taken from literature and on small instances generated similar to that of Cordeau's benchmark instances and validate our solution approach against the optimal solutions obtained through the exact method before implementing it on food rescue and delivery network. Computational experiments indicate that the proposed method outperforms existing heuristics and is able to solve the real-world scenarios using significantly fewer resources than are employed in practice. (C) 2017 Elsevier Ltd. All rights reserved.