Integrated location and routing problems

2015年，运输业占加拿大国内生产总值的4.3%，2014年卡车运输占国内贸易总货运量的72.3%。运输公司必须对艰难的客户要求做出回应：以合适的价格、合适的时间、合适的地点、合适的条件交付好的产品。这些要求直接影响布线距离，从而增加燃料成本。然后，运输公司必须找到降低这些路线成本的方法，同时提高客户的总体满意度。运输企业面临着新的复杂问题，即路线与其他部件的集成，如装载约束和覆盖约束。这项研究计划的长期目标是为这些问题开展基础和算法研究。运用运筹学原理解决这些问题，既是对科学的贡献，也是对行业的贡献。这项研究计划分为三个目标。在每个目标中，科学贡献包括发展适当的方法论，如下：1)识别问题和收集数据，2)开发有效的数学模型，3)实施精确的、启发式和数学式的求解算法，以及4)解决问题和验证结果。该研究计划的第一个目标是解决具有特定装载约束的运输问题，以便限制装卸作业。将开发数学模型以及分支机构定价和削减算法，以提供低燃料成本的解决方案，同时通过降低商品损坏或损坏的风险来提高客户满意度。研究计划的第二个目标是研究添加访问客户子集的选项的影响，并确保每个未访问的客户都在访问的客户的最大覆盖半径内。例如，在多式联运网络中或在偏远地区的医疗供应链中交付用品时，就面临着这个问题。第一个贡献将是在偏远地区的医疗供应链背景下建立满意度模型。第二个贡献将是针对网络的变化制定强有力的解决方案，并制定适当的方法。解决这些问题将直接影响偏远地区人口的复盖率和满意度。研究计划的第三个目标是设计适合不同交通问题的网络。特别是，我们的目标是解决具有装载限制的运输问题的网络和偏远地区的医疗供应链网络。网络的变化可以包括使用转运点，这将减少总的路线成本，并将提高总的客户满意度。

In 2015, the transportation sector represented 4.3% of the canadian Gross Domestic Product and 72.3% of the total volume of goods in domestic trade were transported by trucks in 2014. Transportation companies must respond to difficult customer requirements: delivering the good product, at the right price, at the good time, at the right place, and in the right conditions. These requirements have a direct impact on the routing distance, which increases the fuel costs. Transportation companies must then find methods to decrease these routing costs while increasing the total customer satisfaction. New complex problems where routing is integrated to other components, such as loading constraints and coverage constraints, are faced by transportation companies. The long term objective of this research program is to develop fundamental and algorithmic research for these problems. Addressing these problems with operations research principle is a scientific contribution as well as a contribution for the industry. This research program is divided into three goals. In each goal, scientific contributions include the development of the appropriate methodology which is as follows: 1) identifying the problem and collecting data, 2) developing efficient mathematical models, 3) implementing exact, heuristic, and matheuristic solution algorithms, and 4) solving the problem and validating the results. The first aim of the research program is to address transportation problems with specific loading constraints in order to limit handling operations. Mathematical models as well as branch-price-and-cut algorithms will be developed in order to provide solutions with low fuel costs while increasing customer satisfaction by decreasing the risk of broken or damaged merchandise. The second aim of the research program is to study the impact of adding the option of visiting a subset of customers and making sure that each unvisited customer is within a maximal coverage radius of a visited customer. This problem is faced, for example, in multimodal transportation networks or in the delivery of supplies in healthcare supply chains in remote regions. A first contribution will be to model satisfaction in the context of healthcare supply chains in remote regions. A second contribution will be to develop solutions robust to changes in the network and to develop the appropriate methodology. Addressing these problems will have a direct impact on remote population coverage and satisfaction. The third aim of the research program is to design networks appropriate for different transportation problems. In particular, we aim to address networks for transportation problems with loading constraints and networks for healthcare supply chains in remote regions. Changes in the network could include the use of transshipment points which would decrease the total routing costs and would increase the total customer satisfaction.