Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms

TLDR

The vehicle routing problem with time windows (VRPTW) seeks to design least‑cost routes from a depot to geographically scattered points, ensuring each point is visited once within a specified time window, routes start and end at the depot, and vehicle capacity constraints are respected. This survey reviews VRPTW research and proposes evaluating heuristic methods via Pareto optimality to compare different approaches. The study examines traditional heuristic route‑construction techniques and recent local‑search algorithms, describing their basic features and presenting experimental results on Solomon’s benchmark problems while outlining a Pareto‑based evaluation framework. The article’s second part details the metaheuristic methods explored.

Abstract

This paper presents a survey of the research on the vehicle routing problem with time windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from one depot to a set of geographically scattered points. The routes must be designed in such a way that each point is visited only once by exactly one vehicle within a given time interval, all routes start and end at the depot, and the total demands of all points on one particular route must not exceed the capacity of the vehicle. Both traditional heuristic route construction methods and recent local search algorithms are examined. The basic features of each method are described, and experimental results for Solomon’s benchmark test problems are presented and analyzed. Moreover, we discuss how heuristic methods should be evaluated and propose using the concept of Pareto optimality in the comparison of different heuristic approaches. The metaheuristic methods are described in the second part of this article.