DocumentCode :
3463181
Title :
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
Link To Document :
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