Abstract
The topic of this paper is a Genetic Algorithm solution to the Vehicle Routing Problem with Time Windows, a variant of one of the most common problems in contemporary operations research. The paper will introduce the problem starting with more general Traveling Salesman and Vehicle Routing problems and present some of the prevailing strategies for solving them, focusing on Genetic Algorithms. At the end, it will summarize the Genetic Algorithm solution proposed by K.Q. Zhu which was used in the programming part of the project.
Highlights
Vehicle Routing Problem with Time Windows is a variant of one of the most well known problems in contemporary operations research
Genetic Algorithms (GA for short) are a class of adaptive heuristics based on the Darwinian concept of evolution – “survival of the fittest.”
Blind search which pure GAs offer does not yield best solutions in situations in which we know enough about the problem
Summary
Vehicle Routing Problem with Time Windows is a variant of one of the most well known problems in contemporary operations research. The goal of the problem is to determine an optimal route for delivery of packages to customers who have specified when they will be available to receive their packages, taking into consideration vehicle and package size, and possibly some additional constraints. Interest in the Vehicle Routing Problem (VRP) grew rapidly after World War II, following the increase in postal traffic and catalog ordering of goods from a remote retailer. Vehicle Routing Problem has a historical and theoretical background in the Traveling Salesman Problem; both of these address the problem of finding a minimal cost route within a predefined set of points, given a set of constraints. A GA solution to the Vehicle Routing Problem with Time Windows proposed by K.Q. Zhu [13] will be presented
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