A tabu search method for the truck and trailer routing problem

Abstract A solution construction method and a tabu search improvement heuristic coupled with the deviation concept found in deterministic annealing is developed to solve the truck and trailer routing problem. We test our tabu search method on 21 problems that have been converted from the basic vehicle routing problem. Our construction method always solves a problem (it always finds a feasible solution) and the tabu search improvement heuristic significantly improves an initial solution. Scope and purpose The vehicle routing problem holds a central place in distribution management and logistics, and its practical significance has been well documented in the literature. The truck and trailer routing problem is a variant of the vehicle routing problem to take into account some real-life applications in which fleet of m k trucks and m l trailers ( m k ⩾ m l ) services a set of customers. Some customers can be serviced by a complete vehicle (that is, a truck pulling a trailer) or by a truck alone, whereas others can be serviced only a truck alone. There are three types of routes in a solution to the problem: (1) a pure truck route traveled by a truck alone, (2) a pure vehicle route without any sub-tours traveled by a complete vehicle, and (3) a complete vehicle route consisting of a main tour traveled by a complete vehicle, and one or more sub-tours traveled by a truck alone. A sub-tour begins and finishes at a customer on the main tour where the truck uncouples, parks, and re-couples its pulling trailer and continues to service the remaining customers on the sub-tour. The objective is to minimize the total distance traveled, or total cost incurred by the fleet. The problem is more difficult to solve than the basic vehicle routing problem, but it occurs in many real-life applications. The purpose of this article is to develop a solution method that generates an initial solution and improves the solution using tabu search. The tabu search procedure uses the deviation concept found in deterministic annealing to further improve the initial solution. Our heuristic solves the truck and trailer routing problem efficiently and effectively.

[1]  L. Bodin ROUTING AND SCHEDULING OF VEHICLES AND CREWS–THE STATE OF THE ART , 1983 .

[2]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[3]  Teodor Gabriel Crainic,et al.  Fleet management and logistics , 1998 .

[4]  Bruce L. Golden,et al.  A new heuristic for the multi-depot vehicle routing problem that improves upon best-known solutions , 1993 .

[5]  Yves Rochat,et al.  A Tabu Search Approach for Delivering Pet Food and Flour in Switzerland , 1994 .

[6]  Gilbert Laporte,et al.  The vehicle routing problem: An overview of exact and approximate algorithms , 1992 .

[7]  Graham K. Rand,et al.  Vehicle Routing: Methods and Studies (Studies in Management Science and Systems, Volume 16) , 1988 .

[8]  Bruce L. Golden,et al.  A Computational Study Of A New Heuristic For The Site-Dependent Vehicle Routing Problem , 1999 .

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

[10]  Shen Lin Computer solutions of the traveling salesman problem , 1965 .

[11]  Gerhard W. Dueck,et al.  Threshold accepting: a general purpose optimization algorithm appearing superior to simulated anneal , 1990 .

[12]  Frédéric Semet,et al.  A two-phase algorithm for the partial accessibility constrained vehicle routing problem , 1995, Ann. Oper. Res..

[13]  Nicos Christofides,et al.  The vehicle routing problem , 1976, Revue française d'automatique, informatique, recherche opérationnelle. Recherche opérationnelle.

[14]  A Assad,et al.  VEHICLE ROUTING WITH SITE DEPENDENCIES. VEHICLE ROUTING: METHODS AND STUDIES. STUDIES IN MANAGEMENT SCIENCE AND SYSTEMS - VOLUME 16 , 1988 .

[15]  Nicos Christofides,et al.  Combinatorial optimization , 1979 .

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

[17]  James P. Kelly,et al.  The Impact of Metaheuristics on Solving the Vehicle Routing Problem: Algorithms, Problem Sets, and Computational Results , 1998 .

[18]  Fred W. Glover,et al.  Future paths for integer programming and links to artificial intelligence , 1986, Comput. Oper. Res..

[19]  Roy E. Marsten,et al.  The Design of the XMP Linear Programming Library , 1981, TOMS.

[20]  Éric D. Taillard,et al.  Solving real-life vehicle routing problems efficiently using tabu search , 1993, Ann. Oper. Res..

[21]  Leon S. Lasdon,et al.  Optimization Theory of Large Systems , 1970 .

[22]  Bruce L. Golden,et al.  A new algorithm for site-dependent vehicle routing problem , 1997 .

[23]  Johanna C. Gerdessen,et al.  Vehicle routing problem with trailers , 1996 .

[24]  Bruce L. Golden,et al.  An improved heuristic for the period vehicle routing problem , 1995, Networks.

[25]  G. Dueck New optimization heuristics , 1993 .