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Solving Real-World Vehicle Routing Problems with Evolutionary Algorithms

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Natural Intelligence for Scheduling, Planning and Packing Problems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 250))

Abstract

In this chapter, we present the freight transportation planning component of the in.west project. This system uses an Evolutionary Algorithm with intelligent search operations in order to achieve a high utilization of resources and a minimization of the distance travelled by freight carriers in real-world scenarios. We test our planner rigorously with real-world data and obtain substantial improvements when compared to the original freight plans. Additionally, different settings for the Evolutionary Algorithm are studied with further experiments and their utility is verified with statistical tests.

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Author information

Authors and Affiliations

  1. Distributed Systems Group, University of Kassel, Wilhelmshöher Allee 73, 34121, Kassel, Germany

    Thomas Weise

  2. Micromata GmbH Kassel, Marie-Calm-Straße 3, 34131, Kassel, Germany

    Alexander Podlich

  3. BIBA, Bremer Institut für Produktion und Logistik GmbH, Hochschulring 20, 28359, Bremen, Germany

    Christian Gorldt

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  1. Thomas Weise
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  2. Alexander Podlich
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  3. Christian Gorldt
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  1. School of Computing & Design, Swinburne University of Technology (Sarawak Campus), Jalan Simpang Tiga, 93350, Kuching, Sarawak, Malaysia

    Raymond Chiong  & Sandeep Dhakal  & 

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Weise, T., Podlich, A., Gorldt, C. (2009). Solving Real-World Vehicle Routing Problems with Evolutionary Algorithms. In: Chiong, R., Dhakal, S. (eds) Natural Intelligence for Scheduling, Planning and Packing Problems. Studies in Computational Intelligence, vol 250. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04039-9_2

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  • DOI: https://doi.org/10.1007/978-3-642-04039-9_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04038-2

  • Online ISBN: 978-3-642-04039-9

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