Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/70556
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dc.contributor.authorWarisa Wisittipanichen_US
dc.contributor.authorChanagan Boonyaen_US
dc.date.accessioned2020-10-14T08:33:37Z-
dc.date.available2020-10-14T08:33:37Z-
dc.date.issued2020-07-30en_US
dc.identifier.issn1757899Xen_US
dc.identifier.issn17578981en_US
dc.identifier.other2-s2.0-85090169399en_US
dc.identifier.other10.1088/1757-899X/895/1/012014en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85090169399&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/70556-
dc.description.abstract© Published under licence by IOP Publishing Ltd. This study aims to solve a multi-objective tourist trip design problem (MO-TTDP) in order to simultaneously maximize tourist satisfaction and minimize total traveling cost. The goal is to identify optimal routing for tourist under time window and time horizon constraints. The mathematical model is first presented to find optimal routing under limited budget. However, the exact algorithm cannot find solution with multiple objectives simultaneously. Therefore, this study applies a metaheuristic, called Global Local and Near-Neighbour Particle Swarm Optimization (GLNPSO), to solve the MO-TTDP. Several local search strategies are also proposed to enhance the solution quality. The proposed algorithm is implemented on the real-case study in Chiang Mai City, Thailand. The experimental results show that the proposed algorithm yields a set of diverse and high quality non-dominated solutions.en_US
dc.subjectEngineeringen_US
dc.subjectMaterials Scienceen_US
dc.titleMulti-objective Tourist Trip Design Problem in Chiang Mai Cityen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleIOP Conference Series: Materials Science and Engineeringen_US
article.volume895en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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