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Evolutionary and nature inspired algorithms for solving vehicle routing problems with profits

Trachanatzi Dimitra

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URI: http://purl.tuc.gr/dl/dias/09BEEFF0-41E0-47B8-8521-90A0D264A246
Year 2017
Type of Item Master Thesis
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Bibliographic Citation Dimitra Trachanatzi, "Evolutionary and nature inspired algorithms for solving vehicle routing problems with profits", Master Thesis, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2017 https://doi.org/10.26233/heallink.tuc.68693
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Summary

This master thesis proposes two hybrid algorithms to solve vehicle routing problems with profits. In particular, the Distance Related model is proposed, which involves converting solution coding, from discrete node representation into continuous values, based on the Euclidean distance between successive nodes, and vice versa. This model is integrated into the artificial bee colony algorithm (ABC) and the differential evolution algorithm (DE), such the DRABC and DRDE algorithms are presented. The problems solved by the proposed algorithms are: the team orienteering problem (TOP), the capacitated team orienteering problem (CTOP) and the prize-collecting vehicle routing problem (PCVRP). These problems are used to model the tourist trip design problem (TTDP). It also includes a pioneering approach of the TTDP problem, considering tourist trips design for people in a group with different preferences. To solve the later problem's extension, the N-person Battle of the Sexes game is used, which provides an overall scoring of the nodes of a tour based on the preferences of all group's members.

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