{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:37:12Z","timestamp":1760060232222,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,8,11]],"date-time":"2025-08-11T00:00:00Z","timestamp":1754870400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"CMUP","award":["UIDB\/00144\/2020"],"award-info":[{"award-number":["UIDB\/00144\/2020"]}]},{"name":"Nors Group, S.A.","award":["UIDB\/00144\/2020"],"award-info":[{"award-number":["UIDB\/00144\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AppliedMath"],"abstract":"<jats:p>This work proposes a novel multi-objective genetic algorithm to solve the Periodic Vehicle Routing Problem with Time Windows (PVRPTWs) tailored for sales teams with diverse geographic scales and visit frequency requirements. Unlike existing models, our approach incorporates workload balancing and applies a clustering-based preprocessing step for long-distance routes using multidimensional scaling and fuzzy clustering, improving initial route grouping. When tested on three salesperson profiles (short-, mid-, and long-distance), the model achieved up to a 69% reduction in total travel time compared to a nearest neighbor baseline. These results demonstrate substantial improvements over existing methods and underscore the model\u2019s flexibility and potential for extension to dynamic or real-time sales routing applications.<\/jats:p>","DOI":"10.3390\/appliedmath5030103","type":"journal-article","created":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T07:53:44Z","timestamp":1754985224000},"page":"103","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Genetic Algorithm Optimization of Sales Routes with Time and Workload Objectives"],"prefix":"10.3390","volume":"5","author":[{"given":"Filipa","family":"Costa","sequence":"first","affiliation":[{"name":"Mathematics Centre of the Porto University (CMUP), Department of Mathematics, Science Faculty, University of Porto, 4169-007 Porto, Portugal"},{"name":"Nors, R. Manuel Pinto de Azevedo 711 1\u00b0, 4149-010 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7453-3289","authenticated-orcid":false,"given":"Margarida","family":"Brito","sequence":"additional","affiliation":[{"name":"Mathematics Centre of the Porto University (CMUP), Department of Mathematics, Science Faculty, University of Porto, 4169-007 Porto, Portugal"}]},{"given":"Pedro","family":"Louro","sequence":"additional","affiliation":[{"name":"Nors, R. Manuel Pinto de Azevedo 711 1\u00b0, 4149-010 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0852-8892","authenticated-orcid":false,"given":"S\u00edlvio","family":"Gama","sequence":"additional","affiliation":[{"name":"Mathematics Centre of the Porto University (CMUP), Department of Mathematics, Science Faculty, University of Porto, 4169-007 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,11]]},"reference":[{"key":"ref_1","first-page":"13577","article-title":"Enhancing logistics through a vehicle routing problem with deliveries, pickups, and backhauls","volume":"33","author":"Santos","year":"2025","journal-title":"Int. Trans. Oper. Res."},{"key":"ref_2","first-page":"2033","article-title":"Vehicle routing problem and related algorithms for logistics distribution: A literature review and classification","volume":"22","author":"Konstantakopoulos","year":"2022","journal-title":"Oper. 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