A truck loading problem
A truck loading problem
复制标题
DOI：
10.1016/j.cie.2010.02.008
复制
发表时间：
2010-05
期刊：
影响因子：
--
通讯作者：
Ümit Yüceer;Arif Özakça
中科院分区：
文献类型：
--
作者：
Ümit Yüceer;Arif Özakça
具有m个车厢的车辆将q个不同尺寸的不同产品从源运输到n个不同目的地。操作问题是如何装载车辆的车厢，使得对于给定的目的地路线，补给时间最大化。针对这类问题，建立了一个混合整数线性规划模型。对模型结构的研究表明，子问题可以以加权分布问题的形式得到。因此，一个简单的子算法找到了这个子问题的整数解。主算法将不确定性的区间一分为二，直到它变得足够小。还有另一个子算法通过求解阶段I问题来测试在最终的不确定性区间内是否存在可行解。我们的数值经验表明，其计算效率和质量的解决方案。用这种方法可以在几分之一秒内解决一个大小为30的问题。此外，在82%的随机选择的问题中获得了最优解。
A vehicle with m compartments transports q different products of various sizes from a source to n different destinations. The operational problem is how to load the compartments of the vehicle so that the replenishment time is maximized for a given route of destinations. A mixed integer linear programming model is developed for this class of problems. An investigation of the structure of the model reveals that a subproblem can be obtained in the form of a weighted distribution problem. Consequently, a simple subalgorithm finds an integer solution to this subproblem. The main algorithm bisects the interval of uncertainty until it becomes sufficiently small. There is another subalgorithm to test whether a feasible solution exists in the final interval of uncertainty by solving a Phase I problem. Our numerical experience has shown its computational efficiency and the quality of the solutions obtained. A problem of size 30 can be solved by this method in a fraction of a second. Further, an optimal solution is obtained in 82% of the randomly chosen problems.