Optimizing Service Scheduling by Genetic Algorithm Support Decision-Making in Smart Tourism Destinations

Simple item page
dc.contributor.authorPannee Suanpang
dc.contributor.authorPitchaya Jamjuntr
dc.contributor.correspondenceP. Suanpang; Department of Information Technology, Faculty of Science & Technology, Suan Dusit University, Bangkok, Thailand; email: pannee_sua@dusit.ac.th
dc.date.accessioned2025-03-10T07:34:20Z
dc.date.available2025-03-10T07:34:20Z
dc.date.issued2024
dc.description.abstractSmart tourism destinations are characterised by the integration of advanced technologies and devices to ensure visitors enjoy a seamless and environmentally responsible experience. A key challenge for such destinations lies in efficiently managing and delivering services to meet tourists' expectations while upholding sustainability principles and resource management practices. This study aimed to explore the application of genetic algorithms (GAs) in optimising service scheduling, thereby supporting decision-making processes and enhancing tourism destination services. The research employed a service scheduling methodology that directed the algorithm towards maximising efficiency and customer satisfaction, in contrast to traditional organisational scheduling methods. The methodology centred on the implementation of an algorithmic approach in service delivery management, prioritising operational efficiency and improved customer experience over conventional scheduling techniques. Data collected were systematically analysed, resulting in the development of a theoretical framework based on the findings. The results demonstrated that genetic algorithms significantly enhance service scheduling efficiency when used alongside other methods. The findings underscore the pivotal role of GAs in enabling businesses to achieve time and cost savings while improving customer satisfaction. Furthermore, the study highlights GAs' capacity for adaptability, allowing schedules to be adjusted rapidly in response to changing circumstances, thus providing flexibility and responsiveness to variations in demand. Finally, the research identifies opportunities for innovation and diversification in applying GAs for time scheduling within the tourism sector. It also emphasises the importance of integrating real-time information into scheduling systems to improve service provision at tourist sites. This approach not only enhances the competitiveness of tourism destinations but also adds substantial value to the industry by enriching tourists' experiences and fostering sustainable practices © 2024 Regional Association for Security and crisis management. All rights reserved.
dc.identifier.citationDecision Making: Applications in Management and Engineering
dc.identifier.doi10.31181/dmame7120241273
dc.identifier.issn25606018
dc.identifier.scopus2-s2.0-85215318013
dc.identifier.urihttps://repository.dusit.ac.th//handle/123456789/4473
dc.languageEnglish
dc.publisherRegional Association for Security and crisis management
dc.rights.holderScopus
dc.subjectDecision-making, Smart tourism
dc.subjectGenetic algorithm
dc.subjectOptimizing
dc.subjectService scheduling
dc.titleOptimizing Service Scheduling by Genetic Algorithm Support Decision-Making in Smart Tourism Destinations
dc.typeArticle
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85215318013&doi=10.31181%2fdmame7120241273&partnerID=40&md5=895be8e983a5ee064e94888ddab46a58
oaire.citation.endPage650
oaire.citation.issue1
oaire.citation.startPage624
oaire.citation.volume7
Files
Collections
SCOPUS 2024