{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T04:25:48Z","timestamp":1778214348774,"version":"3.51.4"},"reference-count":24,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,5,17]],"date-time":"2022-05-17T00:00:00Z","timestamp":1652745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["61903227"],"award-info":[{"award-number":["61903227"]}]},{"name":"National Natural Science Foundation of China","award":["2019GGX104105"],"award-info":[{"award-number":["2019GGX104105"]}]},{"name":"Important R&amp;D Program of Shandong, China","award":["61903227"],"award-info":[{"award-number":["61903227"]}]},{"name":"Important R&amp;D Program of Shandong, China","award":["2019GGX104105"],"award-info":[{"award-number":["2019GGX104105"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper proposed an improved Grey Wolf Optimizer (GWO) to resolve the problem of instability and convergence accuracy when GWO is used as a meta-heuristic algorithm with strong optimal search capability in the path planning for mobile robots. We improved chaotic tent mapping to initialize the wolves to enhance the global search ability and used a nonlinear convergence factor based on the Gaussian distribution change curve to balance the global and local searchability. In addition, an improved dynamic proportional weighting strategy is proposed that can update the positions of grey wolves so that the convergence of this algorithm can be accelerated. The proposed improved GWO algorithm results are compared with the other eight algorithms through several benchmark function test experiments and path planning experiments. The experimental results show that the improved GWO has higher accuracy and faster convergence speed.<\/jats:p>","DOI":"10.3390\/s22103810","type":"journal-article","created":{"date-parts":[[2022,5,18]],"date-time":"2022-05-18T03:20:43Z","timestamp":1652844043000},"page":"3810","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":188,"title":["Improved Grey Wolf Optimization Algorithm and Application"],"prefix":"10.3390","volume":"22","author":[{"given":"Yuxiang","family":"Hou","sequence":"first","affiliation":[{"name":"School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China"},{"name":"Shandong Key Laboratory of Intelligent Building Technology, Jinan 250101, China"}]},{"given":"Huanbing","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China"},{"name":"Shandong Key Laboratory of Intelligent Building Technology, Jinan 250101, China"}]},{"given":"Zijian","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China"},{"name":"Shandong Key Laboratory of Intelligent Building Technology, Jinan 250101, China"}]},{"given":"Chuansheng","family":"Du","sequence":"additional","affiliation":[{"name":"School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China"},{"name":"Shandong Key Laboratory of Intelligent Building Technology, Jinan 250101, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.procs.2018.07.018","article-title":"Methodology for path planning and optimization of mobile robots: A review","volume":"133","author":"Zafar","year":"2018","journal-title":"Procedia Comput. 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