{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T14:44:27Z","timestamp":1784126667604,"version":"3.55.0"},"reference-count":26,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2019,6,11]],"date-time":"2019-06-11T00:00:00Z","timestamp":1560211200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51609120"],"award-info":[{"award-number":["51609120"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Plan for Shandong University","award":["J16LB7"],"award-info":[{"award-number":["J16LB7"]}]},{"name":"Key R &amp; D project of Shandong Province","award":["2018YFJH0704"],"award-info":[{"award-number":["2018YFJH0704"]}]},{"name":"Scientific Research Foundation of Chongqing Education Commission","award":["KJ1600509"],"award-info":[{"award-number":["KJ1600509"]}]},{"name":"Foundation and Frontier Projects of Chongqing Science and Technology Commission","award":["cstc2016jcyjA0561"],"award-info":[{"award-number":["cstc2016jcyjA0561"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The genetic algorithm (GA) is an effective method to solve the path-planning problem and help realize the autonomous navigation for and control of unmanned surface vehicles. In order to overcome the inherent shortcomings of conventional GA such as population premature and slow convergence speed, this paper proposes the strategy of increasing the number of offsprings by using the multi-domain inversion. Meanwhile, a second fitness evaluation was conducted to eliminate undesirable offsprings and reserve the most advantageous individuals. The improvement could help enhance the capability of local search effectively and increase the probability of generating excellent individuals. Monte-Carlo simulations for five examples from the library for the travelling salesman problem were first conducted to assess the effectiveness of algorithms. Furthermore, the improved algorithms were applied to the navigation, guidance, and control system of an unmanned surface vehicle in a real maritime environment. Comparative study reveals that the algorithm with multi-domain inversion is superior with a desirable balance between the path length and time-cost, and has a shorter optimal path, a faster convergence speed, and better robustness than the others.<\/jats:p>","DOI":"10.3390\/s19112640","type":"journal-article","created":{"date-parts":[[2019,6,11]],"date-time":"2019-06-11T10:55:44Z","timestamp":1560250544000},"page":"2640","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":109,"title":["An Improved Genetic Algorithm for Path-Planning of Unmanned Surface Vehicle"],"prefix":"10.3390","volume":"19","author":[{"given":"Junfeng","family":"Xin","sequence":"first","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiabao","family":"Zhong","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengru","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0822-7771","authenticated-orcid":false,"given":"Ying","family":"Cui","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinlu","family":"Sheng","sequence":"additional","affiliation":[{"name":"Transport College, Chongqing Jiaotong University, Chongqing 400074, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s10846-012-9805-3","article-title":"A market-based solution to the multiple traveling salesmen problem","volume":"72","author":"Kivelevitch","year":"2013","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.trc.2015.03.005","article-title":"The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery","volume":"54","author":"Murray","year":"2015","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1287\/trsc.2017.0791","article-title":"Optimization approaches for the traveling salesman problem with drone","volume":"52","author":"Agatz","year":"2018","journal-title":"Transp. Sci."},{"key":"ref_4","first-page":"81","article-title":"Towards interactive machine learning (iML): Applying ant colony algorithms to solve the traveling salesman problem with the human-in-the-loop approach","volume":"9817","author":"Holzinger","year":"2016","journal-title":"Availab. Reliab. Secur. Inf. Syst."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.tcs.2016.04.006","article-title":"Traveling salesman problems in temporal graphs","volume":"634","author":"Michail","year":"2016","journal-title":"Theor. Comput. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1007\/s10462-011-9288-9","article-title":"Word sense disambiguation as a traveling salesman problem","volume":"40","author":"Nguyen","year":"2011","journal-title":"Artif. Intell. Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.tre.2016.01.010","article-title":"The electric traveling salesman problem with time windows","volume":"89","author":"Roberti","year":"2016","journal-title":"Transp. Res. Part E Logist. Transp. Rev."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.3390\/s150101245","article-title":"A high fuel consumption efficiency management scheme for PHEVs using an adaptive genetic algorithm","volume":"15","author":"Lee","year":"2015","journal-title":"Sensors"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Tu, W., Xu, X., Ye, T., and Cheng, Z. (2017). A study on wireless charging for prolonging the lifetime of wireless sensor networks. Sensors, 17.","DOI":"10.3390\/s17071560"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1016\/j.pnsc.2008.03.028","article-title":"An ant colony optimization method for generalized TSP problem","volume":"18","author":"Yang","year":"2008","journal-title":"Prog. Nat. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1007\/s10957-007-9308-8","article-title":"A hybrid genetic algorithm with Boltzmann convergence properties","volume":"136","author":"Jackson","year":"2007","journal-title":"J. Optim. Theory Appl."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Lee, H.Y., Shin, H., and Chae, J. (2018). Path planning for mobile agents using a genetic algorithm with a direction guided factor. Electronics, 7.","DOI":"10.3390\/electronics7100212"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.jocs.2017.08.004","article-title":"Bezier curve based path planning in a dynamic field using modified genetic algorithm","volume":"25","author":"Elhoseny","year":"2018","journal-title":"J. Comput. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1007\/s10846-013-9968-6","article-title":"Generation of Bezier curve-based flyable trajectories for multi-UAV systems with parallel genetic algorithm","volume":"74","author":"Sahingoz","year":"2013","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1007\/s10846-013-9895-6","article-title":"3D path planning for multiple UAVs for maximum information collection","volume":"73","author":"Ergezer","year":"2013","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1016\/j.oceaneng.2017.07.040","article-title":"A study on path optimization method of an unmanned surface vehicle under environmental loads using genetic algorithm","volume":"142","author":"Kim","year":"2017","journal-title":"Ocean Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.asoc.2016.02.021","article-title":"Multi-offspring genetic algorithm and its application to the traveling salesman problem","volume":"43","author":"Wang","year":"2016","journal-title":"Appl. Soft Comput."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"47","DOI":"10.3233\/JIFS-172127","article-title":"Multi-objective four dimensional imprecise TSP solved with a hybrid multi-objective ant colony optimization-genetic algorithm with diversity","volume":"36","author":"Khanra","year":"2019","journal-title":"J. Intell. Fuzzy Syst."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Sabino, S., Horta, N., and Grilo, A. (2018). Centralized unmanned aerial vehicle mesh network placement scheme: A multi-objective evolutionary algorithm approach. Sensors, 18.","DOI":"10.3390\/s18124387"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Silva, C.A.D., De Oliveira, \u00c1.V.F.M., and Fernandes, M.A.C. (2018). Validation of a dynamic planning navigation strategy applied to mobile terrestrial robots. Sensors, 18.","DOI":"10.3390\/s18124322"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7313","DOI":"10.1109\/ACCESS.2018.2889737","article-title":"An effective approach for obtaining a group trading strategy portfolio using grouping genetic algorithm","volume":"7","author":"Chen","year":"2019","journal-title":"IEEE Access"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1564","DOI":"10.1016\/j.compeleceng.2012.06.016","article-title":"Dynamic path planning of mobile robots with improved genetic algorithm","volume":"38","author":"Tuncer","year":"2012","journal-title":"Comput. Electr. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1313","DOI":"10.1016\/j.eswa.2010.07.006","article-title":"Development a new mutation operator to solve the traveling salesman problem by aid of genetic algorithms","volume":"38","author":"Albayrak","year":"2011","journal-title":"Expert Syst. Appl."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4369","DOI":"10.1080\/00207540600632190","article-title":"An introduction of dominant genes in genetic algorithm for FMS","volume":"46","author":"Chan","year":"2008","journal-title":"Int. J. Prod. Res."},{"key":"ref_25","first-page":"72","article-title":"A survey on crossover operators","volume":"49","author":"Pavai","year":"2016","journal-title":"ACM Comput. Surv."},{"key":"ref_26","unstructured":"Spear, M.E. (1952). Charting Statistics, McGraw-Hill."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/11\/2640\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:57:32Z","timestamp":1760187452000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/11\/2640"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6,11]]},"references-count":26,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2019,6]]}},"alternative-id":["s19112640"],"URL":"https:\/\/doi.org\/10.3390\/s19112640","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,6,11]]}}}