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.
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