Mathematical programming techniques for the solution of hard combinatorial optimization problems arising in transportation

用于解决运输中出现的硬组合优化问题的数学编程技术

• 批准号: 435824-2013
• 负责人: ContardoVera, Claudio
• 金额: $ 1.6万
• 依托单位: Université du Québec à Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=574193
• 关键词: Mathematical; programming; techniques; solution; hard

This research plan is intended to study several classes of vehicle routing problems with synchronization constraints, to propose modeling approaches and efficient exact and heuristic algorithms. Notably, we consider vehicle routing problems with transfers and multiple-echelon vehicle routing problems. These classes of vehicle routing problems share a common characteristic: either because of synchronization at transfer points or consolidation points, the underlying timing issue plays a crucial role in determining the efficiency of a given solution. Indeed, if the timing issue is not properly handled, one may end with a possibly cheaper solution in terms of traveling time, but much more expensive in terms of total ride time (which includes the dead times due to improper synchronization). The methodological plan can be summarized as follows: First, we seek to develop appropriate mixed-integer models for these classes of vehicle routing problems. We are not interested in just any type of model, but the ones that will allow us to exploit the underlying structure of each problem, either in the context of an exact solver or a heuristic algorithm. For the exact solvers, we will consider known paradigms such as the branch-and-cut method, the column generation framework and Benders decomposition. On the other hand, we will develop heuristic algorithms based on neighborhood search coupled with integer programming methods, the latter being adaptations of the exact methods developed before. We will complement these theoretical and algorithmic developments with actual applications to real-life logistics problems. To that end, we will search for industrial partners that may be interested into applying some of the techniques applied during this research plan to their operational planning.

本研究计划旨在研究几类具有同步约束的车辆路径问题，提出建模方法和高效的精确启发式算法。值得注意的是，我们考虑了换乘车辆路径问题和多梯队车辆路径问题。这些类别的车辆路径问题有一个共同的特征：由于转运点或合并点的同步，潜在的计时问题在确定给定解决方案的效率方面起着至关重要的作用。事实上，如果计时问题处理不当，最终可能会得到一种在行驶时间方面可能更便宜的解决方案，但在总行驶时间方面（包括由于不正确的同步而导致的死区时间）却要昂贵得多。 该方法计划可概括如下：首先，我们寻求为此类车辆路径问题开发适当的混合整数模型。我们不仅仅对任何类型的模型感兴趣，而是对那些能够让我们在精确求解器或启发式算法的背景下利用每个问题的底层结构的模型感兴趣。对于精确求解器，我们将考虑已知的范例，例如分支割法、列生成框架和 Benders 分解。另一方面，我们将开发基于邻域搜索和整数规划方法的启发式算法，后者是之前开发的精确方法的改编。 我们将通过对现实物流问题的实际应用来补充这些理论和算法的发展。为此，我们将寻找可能有兴趣将本研究计划中应用的一些技术应用到其运营规划中的工业合作伙伴。