Multi-objective Tourist Trip Design Problem in Chiang Mai City
© 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...
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th-cmuir.6653943832-705562020-10-14T08:38:19Z Multi-objective Tourist Trip Design Problem in Chiang Mai City Warisa Wisittipanich Chanagan Boonya Engineering Materials Science © 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. 2020-10-14T08:33:37Z 2020-10-14T08:33:37Z 2020-07-30 Conference Proceeding 1757899X 17578981 2-s2.0-85090169399 10.1088/1757-899X/895/1/012014 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85090169399&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/70556 |
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Engineering Materials Science |
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Engineering Materials Science Warisa Wisittipanich Chanagan Boonya Multi-objective Tourist Trip Design Problem in Chiang Mai City |
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© 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. |
format |
Conference Proceeding |
author |
Warisa Wisittipanich Chanagan Boonya |
author_facet |
Warisa Wisittipanich Chanagan Boonya |
author_sort |
Warisa Wisittipanich |
title |
Multi-objective Tourist Trip Design Problem in Chiang Mai City |
title_short |
Multi-objective Tourist Trip Design Problem in Chiang Mai City |
title_full |
Multi-objective Tourist Trip Design Problem in Chiang Mai City |
title_fullStr |
Multi-objective Tourist Trip Design Problem in Chiang Mai City |
title_full_unstemmed |
Multi-objective Tourist Trip Design Problem in Chiang Mai City |
title_sort |
multi-objective tourist trip design problem in chiang mai city |
publishDate |
2020 |
url |
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85090169399&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/70556 |
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