Study of the GELS-GA algorithm on CVRP and its applications
The Capacitated Vehicle Routing Problem (CVRP) is a variant of the VRP problem. The CVRP problem is an optimization problem that can be solved using metaheuristic optimization methods such as Gravitational Emulation Local Search with Genetic Algorithm (GELS-GA). The focus of this article is the impl...
Gespeichert in:
| Veröffentlicht in: | AIP conference proceedings 2022-11, Vol.2639 (1) |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 1 |
| container_start_page | |
| container_title | AIP conference proceedings |
| container_volume | 2639 |
| creator | Aziz, Febri Nur Wahyuningsih, Sapti Satyananda, Darmawan |
| description | The Capacitated Vehicle Routing Problem (CVRP) is a variant of the VRP problem. The CVRP problem is an optimization problem that can be solved using metaheuristic optimization methods such as Gravitational Emulation Local Search with Genetic Algorithm (GELS-GA). The focus of this article is the implementation of the GELS-GA algorithm on CVRP with the Borland Delphi 7 application, tested with several datasets and compared to other algorithms. Program inputs are population size, crossover probability, mutation probability, maximum iteration, vehicle capacity, number of points, and demand for each customer. The program output is in the form of route results with mileage and route images. The results of the trial using 3 VRP datasets consisting of 45 points, 60 points, and 80 points were experimented 10 times with the results compared with the LNS-ACO algorithm. Based on the test results, the GELS-GA solution is better than the LNS-ACO algorithm in the A-n60-k09 code and A-n80-k10 code. In code A-n45-k06 the GELS-GA algorithm does not have a better solution than LNS-ACO. The GELS-GA algorithm on CVRP can be used to solve distribution optimization problems. |
| doi_str_mv | 10.1063/5.0110944 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_scita</sourceid><recordid>TN_cdi_proquest_journals_2731252544</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2731252544</sourcerecordid><originalsourceid>FETCH-LOGICAL-p984-5bb238193dc0a40282ac2a5031d7d98881c0a1788eba5cb5a953c8043e3603183</originalsourceid><addsrcrecordid>eNotkM9LwzAcxYMoWKcH_4OANyEz3_xoUjyNslWhoLgh3kKadq6ja2uTHvbfW91ODx4f3ns8hO6BzoHG_EnOKQBNhLhAEUgJRMUQX6KITh5hgn9doxvv95SyRCkdoed1GMsj7rY47CqcLfM1yRbYNt_dUIfdAXctTj8_3rFtS1wHj23fN7Wzoe5af4uutrbx1d1ZZ2izWm7SF5K_Za_pIid9ogWRRcG4hoSXjlpBmWbWMSsph1KVidYaJh-U1lVhpSukTSR3mgpe8XiCNJ-hh1NsP3Q_Y-WD2Xfj0E6NhikOTDIpxEQ9nijv6vC_z_RDfbDD0QA1f98Yac7f8F9vGVJx</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2731252544</pqid></control><display><type>article</type><title>Study of the GELS-GA algorithm on CVRP and its applications</title><source>AIP Journals Complete</source><creator>Aziz, Febri Nur ; Wahyuningsih, Sapti ; Satyananda, Darmawan</creator><contributor>Nusantara, Toto ; Purwanto ; Hafiizh, Mochammad ; Rahmadani, Desi</contributor><creatorcontrib>Aziz, Febri Nur ; Wahyuningsih, Sapti ; Satyananda, Darmawan ; Nusantara, Toto ; Purwanto ; Hafiizh, Mochammad ; Rahmadani, Desi</creatorcontrib><description>The Capacitated Vehicle Routing Problem (CVRP) is a variant of the VRP problem. The CVRP problem is an optimization problem that can be solved using metaheuristic optimization methods such as Gravitational Emulation Local Search with Genetic Algorithm (GELS-GA). The focus of this article is the implementation of the GELS-GA algorithm on CVRP with the Borland Delphi 7 application, tested with several datasets and compared to other algorithms. Program inputs are population size, crossover probability, mutation probability, maximum iteration, vehicle capacity, number of points, and demand for each customer. The program output is in the form of route results with mileage and route images. The results of the trial using 3 VRP datasets consisting of 45 points, 60 points, and 80 points were experimented 10 times with the results compared with the LNS-ACO algorithm. Based on the test results, the GELS-GA solution is better than the LNS-ACO algorithm in the A-n60-k09 code and A-n80-k10 code. In code A-n45-k06 the GELS-GA algorithm does not have a better solution than LNS-ACO. The GELS-GA algorithm on CVRP can be used to solve distribution optimization problems.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0110944</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Algorithms ; Ant colony optimization ; Datasets ; Gels ; Genetic algorithms ; Heuristic methods ; Optimization ; Route planning ; Vehicle routing</subject><ispartof>AIP conference proceedings, 2022-11, Vol.2639 (1)</ispartof><rights>Author(s)</rights><rights>2022 Author(s). Published by AIP Publishing.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://pubs.aip.org/acp/article-lookup/doi/10.1063/5.0110944$$EHTML$$P50$$Gscitation$$H</linktohtml><link.rule.ids>309,310,314,776,780,785,786,790,4498,23909,23910,25118,27901,27902,76126</link.rule.ids></links><search><contributor>Nusantara, Toto</contributor><contributor>Purwanto</contributor><contributor>Hafiizh, Mochammad</contributor><contributor>Rahmadani, Desi</contributor><creatorcontrib>Aziz, Febri Nur</creatorcontrib><creatorcontrib>Wahyuningsih, Sapti</creatorcontrib><creatorcontrib>Satyananda, Darmawan</creatorcontrib><title>Study of the GELS-GA algorithm on CVRP and its applications</title><title>AIP conference proceedings</title><description>The Capacitated Vehicle Routing Problem (CVRP) is a variant of the VRP problem. The CVRP problem is an optimization problem that can be solved using metaheuristic optimization methods such as Gravitational Emulation Local Search with Genetic Algorithm (GELS-GA). The focus of this article is the implementation of the GELS-GA algorithm on CVRP with the Borland Delphi 7 application, tested with several datasets and compared to other algorithms. Program inputs are population size, crossover probability, mutation probability, maximum iteration, vehicle capacity, number of points, and demand for each customer. The program output is in the form of route results with mileage and route images. The results of the trial using 3 VRP datasets consisting of 45 points, 60 points, and 80 points were experimented 10 times with the results compared with the LNS-ACO algorithm. Based on the test results, the GELS-GA solution is better than the LNS-ACO algorithm in the A-n60-k09 code and A-n80-k10 code. In code A-n45-k06 the GELS-GA algorithm does not have a better solution than LNS-ACO. The GELS-GA algorithm on CVRP can be used to solve distribution optimization problems.</description><subject>Algorithms</subject><subject>Ant colony optimization</subject><subject>Datasets</subject><subject>Gels</subject><subject>Genetic algorithms</subject><subject>Heuristic methods</subject><subject>Optimization</subject><subject>Route planning</subject><subject>Vehicle routing</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNotkM9LwzAcxYMoWKcH_4OANyEz3_xoUjyNslWhoLgh3kKadq6ja2uTHvbfW91ODx4f3ns8hO6BzoHG_EnOKQBNhLhAEUgJRMUQX6KITh5hgn9doxvv95SyRCkdoed1GMsj7rY47CqcLfM1yRbYNt_dUIfdAXctTj8_3rFtS1wHj23fN7Wzoe5af4uutrbx1d1ZZ2izWm7SF5K_Za_pIid9ogWRRcG4hoSXjlpBmWbWMSsph1KVidYaJh-U1lVhpSukTSR3mgpe8XiCNJ-hh1NsP3Q_Y-WD2Xfj0E6NhikOTDIpxEQ9nijv6vC_z_RDfbDD0QA1f98Yac7f8F9vGVJx</recordid><startdate>20221102</startdate><enddate>20221102</enddate><creator>Aziz, Febri Nur</creator><creator>Wahyuningsih, Sapti</creator><creator>Satyananda, Darmawan</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20221102</creationdate><title>Study of the GELS-GA algorithm on CVRP and its applications</title><author>Aziz, Febri Nur ; Wahyuningsih, Sapti ; Satyananda, Darmawan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p984-5bb238193dc0a40282ac2a5031d7d98881c0a1788eba5cb5a953c8043e3603183</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Ant colony optimization</topic><topic>Datasets</topic><topic>Gels</topic><topic>Genetic algorithms</topic><topic>Heuristic methods</topic><topic>Optimization</topic><topic>Route planning</topic><topic>Vehicle routing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aziz, Febri Nur</creatorcontrib><creatorcontrib>Wahyuningsih, Sapti</creatorcontrib><creatorcontrib>Satyananda, Darmawan</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>AIP conference proceedings</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aziz, Febri Nur</au><au>Wahyuningsih, Sapti</au><au>Satyananda, Darmawan</au><au>Nusantara, Toto</au><au>Purwanto</au><au>Hafiizh, Mochammad</au><au>Rahmadani, Desi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Study of the GELS-GA algorithm on CVRP and its applications</atitle><jtitle>AIP conference proceedings</jtitle><date>2022-11-02</date><risdate>2022</risdate><volume>2639</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>The Capacitated Vehicle Routing Problem (CVRP) is a variant of the VRP problem. The CVRP problem is an optimization problem that can be solved using metaheuristic optimization methods such as Gravitational Emulation Local Search with Genetic Algorithm (GELS-GA). The focus of this article is the implementation of the GELS-GA algorithm on CVRP with the Borland Delphi 7 application, tested with several datasets and compared to other algorithms. Program inputs are population size, crossover probability, mutation probability, maximum iteration, vehicle capacity, number of points, and demand for each customer. The program output is in the form of route results with mileage and route images. The results of the trial using 3 VRP datasets consisting of 45 points, 60 points, and 80 points were experimented 10 times with the results compared with the LNS-ACO algorithm. Based on the test results, the GELS-GA solution is better than the LNS-ACO algorithm in the A-n60-k09 code and A-n80-k10 code. In code A-n45-k06 the GELS-GA algorithm does not have a better solution than LNS-ACO. The GELS-GA algorithm on CVRP can be used to solve distribution optimization problems.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0110944</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0094-243X |
| ispartof | AIP conference proceedings, 2022-11, Vol.2639 (1) |
| issn | 0094-243X 1551-7616 |
| language | eng |
| recordid | cdi_proquest_journals_2731252544 |
| source | AIP Journals Complete |
| subjects | Algorithms Ant colony optimization Datasets Gels Genetic algorithms Heuristic methods Optimization Route planning Vehicle routing |
| title | Study of the GELS-GA algorithm on CVRP and its applications |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T08%3A51%3A40IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_scita&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Study%20of%20the%20GELS-GA%20algorithm%20on%20CVRP%20and%20its%20applications&rft.jtitle=AIP%20conference%20proceedings&rft.au=Aziz,%20Febri%20Nur&rft.date=2022-11-02&rft.volume=2639&rft.issue=1&rft.issn=0094-243X&rft.eissn=1551-7616&rft.coden=APCPCS&rft_id=info:doi/10.1063/5.0110944&rft_dat=%3Cproquest_scita%3E2731252544%3C/proquest_scita%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2731252544&rft_id=info:pmid/&rfr_iscdi=true |