Heuristic and exact methods applied to a rich vehicle routing and scheduling problem
Naval Architecture and Ocean Engineering of the University of São Paulo to attain the Degree of the Doctorate Program in Naval Architecture and Ocean Engineering. Knowledge Area: Naval and Ocean Engineering. Advisor: Prof. Dr. André Bergsten Mendes São Paulo 2013 FICHA CATALOGRÁFICA Seixas, Michel Povlovitsch Heuristic and exact methods applied to a rich vehicle Routing and scheduling problem / M.P. Seixas. --versão corr. --São Paulo, 2013. 126 p. Tese (Doutorado) -Mendes São Paulo 2013 FICHA
... Paulo 2013 FICHA CATALOGRÁFICA Seixas, Michel Povlovitsch Heuristic and exact methods applied to a rich vehicle Routing and scheduling problem / M.P. Seixas. --versão corr. --São Paulo, 2013. 126 p. Tese (Doutorado) -Acknowledgments I am very thankful to my mother and my father for respecting my decisions and being so supportive. I am grateful to all my closest friends. Special thanks to Rogério Aversa for encouraging me to start this research. Many thanks to Prof. André Mendes for guiding this research, providing milestones, important references and insights and for being so supportive during all these years. I am also very thankful to Prof. Marco Brinati for the rich discussions and relevant insights since the beginning of this research. Thanks to the lecturers and professors of both Polytechnic School of the University of São Paulo and Mathematics and Statistics Institute of the University of São Paulo, who shared their valuable knowledge and made possible the achievements of this research. Abstract This study considers a vehicle routing problem with time windows, accessibility restrictions on customers and a fleet that is heterogeneous with regard to capacity, average speed and cost. A vehicle can perform multiple routes per day, all starting and ending at a single depot, and it is assigned to a single driver, whose total work hours are limited. The available fleet is divided into an owned fleet, for which a variable cost is incurred, and a chartered fleet, for which only a fixed cost is incurred for each vehicle used. A column generation algorithm embedded in a branch-and-bound framework is proposed. The column generation pricing subproblem required a specific elementary shortest path problem with resource constraints algorithm to address the possibility for each vehicle performing multiple routes per day and to address the need to determine the workday's start time within the planning horizon. To make the algorithm efficient, a constructive heuristic and a learning metaheuristic algorithm based on tabu search were also developed. Both were used on branch-and-bound tree nodes to generate a good initial solution to the linear restricted master problem; particularly, to find a good initial primal bound to the branch-and-bound tree.