Integrated location and routing problems

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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.