Genetic algorithm for the one-commodity pickup-and-delivery vehicle routing problem
A new variant of classical VRP, called 1-PDVRP, is introduced in this paper. It differs from the general VRP with pickup and delivery in that the commodity provided by the pickup customers is the same as that needed by delivery customers. We established the mathematical model for 1-PDVRP, and utiliz...
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creator | Xiaoyan Shi Fanggeng Zhao Yancheng Gong |
description | A new variant of classical VRP, called 1-PDVRP, is introduced in this paper. It differs from the general VRP with pickup and delivery in that the commodity provided by the pickup customers is the same as that needed by delivery customers. We established the mathematical model for 1-PDVRP, and utilized genetic algorithm to solve it. In the proposed genetic algorithm, we implemented a pheromone-based crossover operator for this problem and the algorithm is tested on 100 randomly generated instances. |
doi_str_mv | 10.1109/ICICISYS.2009.5357913 |
format | Conference Proceeding |
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In the proposed genetic algorithm, we implemented a pheromone-based crossover operator for this problem and the algorithm is tested on 100 randomly generated instances.</description><subject>Automobiles</subject><subject>Genetic algorithm</subject><subject>Genetic algorithms</subject><subject>Greedy algorithms</subject><subject>Heuristic algorithms</subject><subject>Instruments</subject><subject>Mathematical model</subject><subject>Pheromone-based crossover</subject><subject>Pickup-and-delivery</subject><subject>Routing</subject><subject>Testing</subject><subject>Traveling salesman problems</subject><subject>Vehicle routing problem</subject><subject>Vehicles</subject><isbn>9781424447541</isbn><isbn>1424447542</isbn><isbn>9781424447381</isbn><isbn>1424447380</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpNUE1Lw0AUXJGCWvMLRNg_kLhvP7LZoxRtCwUP1YOnstm8NKtJNmzTQv-9EXtw5jDM8HgMQ8gjsAyAmaf1YuL2c5txxkymhNIGxBVJjC5AcimlFgVc__dKwozc_Z4bpsCwG5IcDl9sglQCuLgl2yX2OHpHbbsP0Y9NR-sQ6dggDT2mLnRdqPx4poN338chtX2VVtj6E8YzPWHjXYs0huPo-z0dYihb7O7JrLbtAZOLzsnH68v7YpVu3pbrxfMm9cDUmFZSGFGjdVxIgLrMlQbmNKt4aXWhLIAqS53DFBtba7BTaVcZzLkseWG0mJOHv78eEXdD9J2N591lF_EDekZVUw</recordid><startdate>200911</startdate><enddate>200911</enddate><creator>Xiaoyan Shi</creator><creator>Fanggeng Zhao</creator><creator>Yancheng Gong</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200911</creationdate><title>Genetic algorithm for the one-commodity pickup-and-delivery vehicle routing problem</title><author>Xiaoyan Shi ; Fanggeng Zhao ; Yancheng Gong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i105t-d4393feac23411fb65710c70d2ba785a115bb7615719af71a045cd9e624b28973</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Automobiles</topic><topic>Genetic algorithm</topic><topic>Genetic algorithms</topic><topic>Greedy algorithms</topic><topic>Heuristic algorithms</topic><topic>Instruments</topic><topic>Mathematical model</topic><topic>Pheromone-based crossover</topic><topic>Pickup-and-delivery</topic><topic>Routing</topic><topic>Testing</topic><topic>Traveling salesman problems</topic><topic>Vehicle routing problem</topic><topic>Vehicles</topic><toplevel>online_resources</toplevel><creatorcontrib>Xiaoyan Shi</creatorcontrib><creatorcontrib>Fanggeng Zhao</creatorcontrib><creatorcontrib>Yancheng Gong</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Xiaoyan Shi</au><au>Fanggeng Zhao</au><au>Yancheng Gong</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Genetic algorithm for the one-commodity pickup-and-delivery vehicle routing problem</atitle><btitle>2009 IEEE International Conference on Intelligent Computing and Intelligent Systems</btitle><stitle>ICICISYS</stitle><date>2009-11</date><risdate>2009</risdate><volume>1</volume><spage>175</spage><epage>179</epage><pages>175-179</pages><isbn>9781424447541</isbn><isbn>1424447542</isbn><eisbn>9781424447381</eisbn><eisbn>1424447380</eisbn><abstract>A new variant of classical VRP, called 1-PDVRP, is introduced in this paper. It differs from the general VRP with pickup and delivery in that the commodity provided by the pickup customers is the same as that needed by delivery customers. We established the mathematical model for 1-PDVRP, and utilized genetic algorithm to solve it. In the proposed genetic algorithm, we implemented a pheromone-based crossover operator for this problem and the algorithm is tested on 100 randomly generated instances.</abstract><pub>IEEE</pub><doi>10.1109/ICICISYS.2009.5357913</doi><tpages>5</tpages></addata></record> |
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subjects | Automobiles Genetic algorithm Genetic algorithms Greedy algorithms Heuristic algorithms Instruments Mathematical model Pheromone-based crossover Pickup-and-delivery Routing Testing Traveling salesman problems Vehicle routing problem Vehicles |
title | Genetic algorithm for the one-commodity pickup-and-delivery vehicle routing problem |
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