Optimizing routes and stock

This work is motivated by a problem proposed to the authors by a bakery company in Northern Spain. The objective is to design the daily routes over the week in order to minimize the total traveled distance. For reducing this total distance, some flexibility in the dates of delivery is introduced, which will cause a stock. Therefore, we study the problem under the bi-objective perspective, “minimizing” simultaneously the total traveled distance and the stock. A bi-objective mixed-integer linear model for the problem is formulated and two methodologies of solution are presented. The first one is based on a series of linked variable neighborhood searches and the second one is based on NSGA-II provided of specific operators. Numerical results showing the obtained estimated Pareto front in both cases are presented.

[1]  Nicolas Jozefowiez,et al.  Multi-objective vehicle routing problems , 2008, Eur. J. Oper. Res..

[2]  Christian Prins,et al.  A simple and effective evolutionary algorithm for the vehicle routing problem , 2004, Comput. Oper. Res..

[3]  Rafael Caballero,et al.  Solving a multiobjective location routing problem with a metaheuristic based on tabu search. Application to a real case in Andalusia , 2007, Eur. J. Oper. Res..

[4]  Nicolas Jozefowiez,et al.  From Single-Objective to Multi-Objective Vehicle Routing Problems: Motivations, Case Studies, and Methods , 2008 .

[5]  Paolo Toth,et al.  The Vehicle Routing Problem , 2002, SIAM monographs on discrete mathematics and applications.

[6]  Bruce L. Golden,et al.  The vehicle routing problem : latest advances and new challenges , 2008 .

[7]  John E. Beasley,et al.  Route first--Cluster second methods for vehicle routing , 1983 .

[8]  Michel Gendreau,et al.  A Tabu Search Heuristic for the Vehicle Routing Problem with Soft Time Windows , 1997, Transp. Sci..

[9]  J Potvin,et al.  A tabu search heuristic for the vehicle routing problem with time windows , 1992 .

[10]  Marshall L. Fisher,et al.  A generalized assignment heuristic for vehicle routing , 1981, Networks.

[11]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[12]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[13]  Paolo Toth,et al.  Knapsack Problems: Algorithms and Computer Implementations , 1990 .

[14]  David K. Smith Network Flows: Theory, Algorithms, and Applications , 1994 .

[15]  Paolo Toth,et al.  Models, relaxations and exact approaches for the capacitated vehicle routing problem , 2002, Discret. Appl. Math..

[16]  Joaquín A. Pacheco,et al.  Optimizing vehicle routes in a bakery company allowing flexibility in delivery dates , 2012, J. Oper. Res. Soc..

[17]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[18]  Matthias Ehrgott,et al.  Multicriteria Optimization , 2005 .

[19]  Carlos Romero,et al.  Teoría de la decisión multicriterio: conceptos, técnicas y aplicaciones , 1993 .

[20]  Gilbert Laporte,et al.  A Tabu Search Heuristic for the Vehicle Routing Problem , 1991 .

[21]  Jon Jouis Bentley,et al.  Fast Algorithms for Geometric Traveling Salesman Problems , 1992, INFORMS J. Comput..