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Title

Application of Industry 3.5 approach for planning of more sustainable supply chain operations for tourism service providers

Authors

[ 1 ] Instytut Logistyki, Wydział Inżynierii Zarządzania, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[5.6] Management and quality studies

Year of publication

2022

Published in

International Journal of Logistics Research and Applications

Journal year: 2022 | Journal volume: in press | Journal number: in press

Article type

scientific article

Publication language

english

Keywords
EN
  • Tourism industry
  • Industry 3.5
  • AI heuristics for optimisation
  • sustainable supply chain management
Abstract

EN This paper addresses a tourist trip design problem and a tour route planning problem to improve the competitiveness of community tourism. The problem was investigated with the objective to maximise the total number of tourists interested in visiting multiple points of interest and several specific activities to receive a satisfactory service by matching their preferences. To solve this problem, a mixed-integer linear programming model was developed for small-size problems, while the modified differential evolution with K-variable moves and random variable neighbourhood search (MDE–RVNS) was developed to determine near-optimal solutions for real problems. To assist the tourism service provider to schedule and sequence the trip and route planning for the tourists, a tourism service provider scheduling and sequencing software based on the MDE-RVNS was designed and developed. A mobile application using the software has been planned for launching to assist tour route planning decisionmakers. This can help local tourism businesses to manage demands and ensure that the tourism revenue is evenly distributed in a tourism supply chain to enhance the well-being of local communities

Pages (from - to)

1 - 24

DOI

10.1080/13675567.2022.2090529

URL

https://doi.org/10.1080/13675567.2022.2090529

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Access level to full text

public

Points of MNiSW / journal

70.0

Impact Factor

3.821 [List 2020]

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