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货物总量的72.3%。运输公司必须对客户的困难要求做出反应：在合适的时间、合适的地点和合适的条件下，以合适的价格交付优质的产品。这些要求对路线距离有直接影响，从而增加了燃料成本。运输公司必须找到方法来降低这些路线成本，同时提高客户的总体满意度。运输公司面临着新的复杂问题，其中路由与其他组件集成，例如装载约束和覆盖约束。该研究计划的长期目标是针对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。这个研究项目分为三个目标。在每个目标中，科学贡献包括开发适当的方法，具体如下：1)识别问题并收集数据，2)开发有效的数学模型，3)实现精确的，启发式的和数学的解决算法，以及4)解决问题并验证结果。研究计划的第一个目的是解决运输问题与特定的装载限制，以限制处理操作。数学模型以及分支价格削减算法将被开发出来，以提供低燃料成本的解决方案，同时通过降低商品破损或损坏的风险来提高客户满意度。研究计划的第二个目的是研究增加访问客户子集的选项并确保每个未访问的客户都在访问客户的最大覆盖半径内的影响。例如，在多式联运网络或偏远地区医疗保健供应链的供应中，都面临着这一问题。第一个贡献将是在偏远地区医疗保健供应链的背景下建立满意度模型。第二个贡献将是开发健壮的解决方案，以适应网络的变化，并开发适当的方法。解决这些问题将对偏远地区人口的覆盖率和满意度产生直接影响。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网络和偏远地区医疗保健供应链网络。网络的变化可以包括使用转运点，这将减少总路线成本，并将提高总体客户满意度。

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.