Scheduling periodic customer visits for a traveling salesperson
The problem considered in this paper deals with determining daily routes for a traveling salesperson who provides customers in Upper Austria with product range information of a large, global food wholesaler. Each customer has to be visited at least once a year, with some customers requiring up to on...
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Veröffentlicht in: | European journal of operational research 2007-06, Vol.179 (3), p.823-837 |
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container_title | European journal of operational research |
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creator | Polacek, Michael Doerner, Karl F. Hartl, Richard F. Kiechle, Guenter Reimann, Marc |
description | The problem considered in this paper deals with determining daily routes for a traveling salesperson who provides customers in Upper Austria with product range information of a large, global food wholesaler. Each customer has to be visited at least once a year, with some customers requiring up to one visit per month. Further, some customers may not be visited each day of the week. Our decision support system uses a commercial GIS software to extract customer data for input into the optimization procedure and to visualize the results obtained by the algorithm. The optimization approach is based on the variable neighborhood search algorithm which assigns customers to days and determines routes for the salesperson for each day with the primary objective to minimize the total travel time of the salesperson. Another objective studied is to minimize the number of days needed by the salesperson to visit all customers in a given month. Further we analyze the effects of changes in the business environment like increases in the amount or flexibility of the salesperson’s working time and variations in the possible days for customer visits. Finally, we enrich the objective function by considering periodicity requirements for customer visits. Specifically, we penalize irregular schedules, where the time between two successive customer visits varies. |
doi_str_mv | 10.1016/j.ejor.2005.03.056 |
format | Article |
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Each customer has to be visited at least once a year, with some customers requiring up to one visit per month. Further, some customers may not be visited each day of the week. Our decision support system uses a commercial GIS software to extract customer data for input into the optimization procedure and to visualize the results obtained by the algorithm. The optimization approach is based on the variable neighborhood search algorithm which assigns customers to days and determines routes for the salesperson for each day with the primary objective to minimize the total travel time of the salesperson. Another objective studied is to minimize the number of days needed by the salesperson to visit all customers in a given month. Further we analyze the effects of changes in the business environment like increases in the amount or flexibility of the salesperson’s working time and variations in the possible days for customer visits. Finally, we enrich the objective function by considering periodicity requirements for customer visits. Specifically, we penalize irregular schedules, where the time between two successive customer visits varies.</description><subject>Customers</subject><subject>Decision support systems</subject><subject>Geographic information systems</subject><subject>Periodic</subject><subject>Real world problem</subject><subject>Studies</subject><subject>Traveling salesman problem</subject><subject>Traveling salesperson problem</subject><subject>Variable neighborhood search</subject><issn>0377-2217</issn><issn>1872-6860</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNp9kN1LwzAUxYMoOKf_gE_F99Z8tEkLgsjwCwc-qM8hu7l1KdtSk3aw_97MiY9eOPe-_M5JOIRcMlowyuR1V2DnQ8EprQoqClrJIzJhteK5rCU9JhMqlMo5Z-qUnMXYUUpZxaoJuX2DJdpx5TafWY_BeesggzEOfo0h27rohpi1PmQmG4LZ4g8YzQpjoqPfnJOT1qwiXvzeKfl4uH-fPeXz18fn2d08h7JshhyRQ8ka4Mo2i1rKhakWAI2wUlluOTW2bCoBaBqObduWgAhMlq1ECRIYFVNydcjtg_8aMQ6682PYpCc1pyUTTVXtIX6AIPgYA7a6D25twk4zqvc96U7ve9L7njQVOvWUTC8HU8Ae4c-BaRKKUW-1MEw1ae-SklWl45JEUp9Uc6FrofRyWKe0m0MapjK2DoOO4HADaF1AGLT17r_PfAMdUYwI</recordid><startdate>20070616</startdate><enddate>20070616</enddate><creator>Polacek, Michael</creator><creator>Doerner, Karl F.</creator><creator>Hartl, Richard F.</creator><creator>Kiechle, Guenter</creator><creator>Reimann, Marc</creator><general>Elsevier B.V</general><general>Elsevier</general><general>Elsevier Sequoia S.A</general><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20070616</creationdate><title>Scheduling periodic customer visits for a traveling salesperson</title><author>Polacek, Michael ; Doerner, Karl F. ; Hartl, Richard F. ; Kiechle, Guenter ; Reimann, Marc</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c449t-ee2c419c27d9b866ba5bcc93d67d2d20ad4953cea92efff4ceec164f6e6c6c103</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Customers</topic><topic>Decision support systems</topic><topic>Geographic information systems</topic><topic>Periodic</topic><topic>Real world problem</topic><topic>Studies</topic><topic>Traveling salesman problem</topic><topic>Traveling salesperson problem</topic><topic>Variable neighborhood search</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Polacek, Michael</creatorcontrib><creatorcontrib>Doerner, Karl F.</creatorcontrib><creatorcontrib>Hartl, Richard F.</creatorcontrib><creatorcontrib>Kiechle, Guenter</creatorcontrib><creatorcontrib>Reimann, Marc</creatorcontrib><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>European journal of operational research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Polacek, Michael</au><au>Doerner, Karl F.</au><au>Hartl, Richard F.</au><au>Kiechle, Guenter</au><au>Reimann, Marc</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Scheduling periodic customer visits for a traveling salesperson</atitle><jtitle>European journal of operational research</jtitle><date>2007-06-16</date><risdate>2007</risdate><volume>179</volume><issue>3</issue><spage>823</spage><epage>837</epage><pages>823-837</pages><issn>0377-2217</issn><eissn>1872-6860</eissn><coden>EJORDT</coden><abstract>The problem considered in this paper deals with determining daily routes for a traveling salesperson who provides customers in Upper Austria with product range information of a large, global food wholesaler. Each customer has to be visited at least once a year, with some customers requiring up to one visit per month. Further, some customers may not be visited each day of the week. Our decision support system uses a commercial GIS software to extract customer data for input into the optimization procedure and to visualize the results obtained by the algorithm. The optimization approach is based on the variable neighborhood search algorithm which assigns customers to days and determines routes for the salesperson for each day with the primary objective to minimize the total travel time of the salesperson. Another objective studied is to minimize the number of days needed by the salesperson to visit all customers in a given month. Further we analyze the effects of changes in the business environment like increases in the amount or flexibility of the salesperson’s working time and variations in the possible days for customer visits. Finally, we enrich the objective function by considering periodicity requirements for customer visits. Specifically, we penalize irregular schedules, where the time between two successive customer visits varies.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.ejor.2005.03.056</doi><tpages>15</tpages></addata></record> |
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source | RePEc; Elsevier ScienceDirect Journals |
subjects | Customers Decision support systems Geographic information systems Periodic Real world problem Studies Traveling salesman problem Traveling salesperson problem Variable neighborhood search |
title | Scheduling periodic customer visits for a traveling salesperson |
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