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Description
  • This work proposes a genetic programming approach for producing an improved Clarke-Wright savings algorithm (CW) for solving capacitated vehicle routing problem (CVRP). CW is a very popular and fast low-level constructive heuristic which uses saving value, defined between each pair of two cities, to construct solutions for CVRP. The main idea of the proposed approach is to use genetic programming (GP) for evolving new mathematical functions for calculating the saving between each pair of cities. CW algorithm with the evolved function is tested on BranchAndCut VRP benchmarks. The results are promising and show improvement on the more than half of test instances.
  • This work proposes a genetic programming approach for producing an improved Clarke-Wright savings algorithm (CW) for solving capacitated vehicle routing problem (CVRP). CW is a very popular and fast low-level constructive heuristic which uses saving value, defined between each pair of two cities, to construct solutions for CVRP. The main idea of the proposed approach is to use genetic programming (GP) for evolving new mathematical functions for calculating the saving between each pair of cities. CW algorithm with the evolved function is tested on BranchAndCut VRP benchmarks. The results are promising and show improvement on the more than half of test instances. (en)
Title
  • Improving Clarke-Wright Algorithm with Genetic Programming
  • Improving Clarke-Wright Algorithm with Genetic Programming (en)
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  • Improving Clarke-Wright Algorithm with Genetic Programming
  • Improving Clarke-Wright Algorithm with Genetic Programming (en)
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  • RIV/68407700:21230/14:00219995!RIV15-MSM-21230___
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  • 20997
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  • RIV/68407700:21230/14:00219995
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  • Hyper-Heuristics; Genetic Programming; Clarke-Wright Savings Algorithm (en)
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  • [C46BF51B968D]
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  • Demänovská Dolina
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  • Proceedings of the 14th conference ITAT 2014 – Workshops and Posters
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  • Hruška, František
  • Kubalík, Jiří
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  • Ústav informatiky AV ČR
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  • 978-80-87136-19-5
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  • 21230
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