Solving large-scale vehicle routing problem instances using an island-model offspring selection genetic algorithm

Author

Vonolfen, Stefan ; Affenzeller, Michael ; Beham, Andreas ; Wagner, Stefan

Author_Institution

Sch. of Inf., Commun. & Media, Upper Austria Univ. of Appl. Sci., Hagenberg, Austria

fYear

2011

fDate

25-27 Aug. 2011

Firstpage

27

Lastpage

31

Abstract

The vehicle routing problem is a class of problems that frequently occurs in the field of transportation logistics. In this work, we tackle very-large scale problem instances with time windows. Among other techniques, metaheuristics are frequently used to solve large-scale instances close to optimality. We present an island-model genetic algorithm variant and apply several techniques such as offspring selection and adaptive constraint relaxation. To validate our approach, we perform test runs on benchmark instances with 1000 customers and compare the results to the currently best-known solutions.

Keywords

genetic algorithms; mobile radio; telecommunication network routing; adaptive constraint relaxation; island-model offspring selection genetic algorithm; large-scale vehicle routing problem; metaheuristic technique; transportation logistic field; Computers; Encoding; Genetic algorithms; Genetics; Routing; Search problems; Vehicles; Vehicle routing problem; island-model genetic algorithm; offspring selection;

fLanguage

English

Publisher

ieee

Conference_Titel

Logistics and Industrial Informatics (LINDI), 2011 3rd IEEE International Symposium on

Conference_Location

Budapest

Print_ISBN

978-1-4577-1842-7

Type

conf

DOI

10.1109/LINDI.2011.6031155

Filename

6031155