{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:45:29Z","timestamp":1776811529679,"version":"3.51.2"},"reference-count":9,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2022,9,5]]},"abstract":"<jats:p>The management of components ensures that the port equipment is in good working condition, ensure port production safety and continuity. In this paper, a port equipment component supply network optimization model that considers the characteristics of shipping network is proposed to optimize hub port selection, route choice, ship deployment, inventory optimization, etc. At the same time, an improved genetic algorithm is developed, including chromosome matrix, row column crossover genetic operation, and double-layer parallel search. The results show that the model and algorithm can effectively obtain a better solution and achieve the optimization goal.<\/jats:p>","DOI":"10.3233\/jcm-226128","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T12:13:12Z","timestamp":1653999192000},"page":"1583-1590","source":"Crossref","is-referenced-by-count":2,"title":["Shipping network optimization of port equipment components based on improved genetic algorithm"],"prefix":"10.66113","volume":"22","author":[{"given":"Huaidong","family":"Li","sequence":"first","affiliation":[{"name":"Zhenhua Heavy Industries Co., Ltd., Shanghai, China"},{"name":"Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiankun","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bangyu","family":"Tong","sequence":"additional","affiliation":[{"name":"China United Engineering Corporation Limited., Hangzhou, Zhejiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","reference":[{"issue":"6","key":"10.3233\/JCM-226128_ref1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ijpe.2018.04.015","article-title":"Modeling and long-term forecasting demand in spare parts logistics businesses","volume":"201","author":"Dombi","year":"2018","journal-title":"Int J Prod Econ."},{"issue":"4","key":"10.3233\/JCM-226128_ref2","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.eswa.2016.12.013","article-title":"A hybrid genetic algorithm for a home health care routing problem with time window and fuzzy demand","volume":"72","author":"Shi","year":"2017","journal-title":"Expert Syst Appl."},{"issue":"6","key":"10.3233\/JCM-226128_ref3","first-page":"1417","article-title":"Combined maintenance and spare supply strategy of unrepairable product","volume":"42","author":"Lin","year":"2020","journal-title":"Syst Eng Electr."},{"issue":"4","key":"10.3233\/JCM-226128_ref4","first-page":"441","article-title":"Optimization method for spare parts transportation route considering reliability index","volume":"44","author":"Zhao","year":"2020","journal-title":"J Nanjing Univ Sci Technol."},{"issue":"1","key":"10.3233\/JCM-226128_ref5","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.ejor.2011.05.057","article-title":"Optimal operating strategy for a long-haul liner service route","volume":"215","author":"Qiang","year":"2011","journal-title":"Eur J Oper Res."},{"issue":"12","key":"10.3233\/JCM-226128_ref6","first-page":"60","article-title":"Network design, fleet deployment and empty repositioning in liner shipping","volume":"108","author":"Rnm","year":"2017","journal-title":"Transp Res Part E: Logistics Transp Rev."},{"issue":"2","key":"10.3233\/JCM-226128_ref7","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1016\/j.tre.2011.10.011","article-title":"Liner ship fleet deployment with container transshipment operations","volume":"48","author":"Wang","year":"2012","journal-title":"Transp Res Part E."},{"issue":"9","key":"10.3233\/JCM-226128_ref8","first-page":"273","article-title":"Sustainable tire closed-loop supply chain network design: Hybrid metaheuristic algorithms for large-scale networks","volume":"196","author":"Navid","year":"2018","journal-title":"J Cleaner Prod."},{"issue":"8","key":"10.3233\/JCM-226128_ref9","doi-asserted-by":"crossref","first-page":"4297","DOI":"10.1007\/s00500-016-2062-9","article-title":"A new cuckoo search algorithm with hybrid strategies for flow shop scheduling problems","volume":"85","author":"Wang","year":"2017","journal-title":"Soft Comput."}],"container-title":["Journal of Computational Methods in Sciences and Engineering"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JCM-226128","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:06:29Z","timestamp":1776809189000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JCM-226128"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,5]]},"references-count":9,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.3233\/jcm-226128","relation":{},"ISSN":["1472-7978","1875-8983"],"issn-type":[{"value":"1472-7978","type":"print"},{"value":"1875-8983","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,5]]}}}