Study of Optimization of Tourists' Travel Paths by Several Algorithms

The purpose of this paper is to optimize the tourism path to make the distance shorter. The article first constructed a model for tourism route planning and then used particle swarm optimization (PSO), genetic algorithm (GA), and ant colony algorithms to solve the model separately. Finally, a simulation experiment was conducted on tourist attractions in the suburbs of Taiyuan City to compare the path optimization performance of the three algorithms. The three path optimization algorithms all converged during the process of finding the optimal path. Among them, the ant colony algorithm exhibited the fastest and most stable convergence, resulting in the smallest model fitness value. The travel route obtained through the ant colony algorithm had the shortest distance, and this algorithm required minimal time for optimization. The novelty of this article lies in the enumeration and description of various algorithms used for optimizing travel paths, as well as the comparison of three different travel route optimization algorithms through simulation experiments. Doi: 10.28991/HIJ-2023-04-02-012 Full Text: PD

Advances in Computer Science and Engineering

The book Advances in Computer Science and Engineering constitutes the revised selection of 23 chapters written by scientists and researchers from all over the world. The chapters cover topics in the scientific fields of Applied Computing Techniques, Innovations in Mechanical Engineering, Electrical Engineering and Applications and Advances in Applied Modeling

Geo Data Science for Tourism

This reprint describes the recent challenges in tourism seen from the point of view of data science. Thanks to the use of the most popular Data Science concepts, you can easily recognise trends and patterns in tourism, detect the impact of tourism on the environment, and predict future trends in tourism. This reprint starts by describing how to analyse data related to the past, then it moves on to detecting behaviours in the present, and, finally, it describes some techniques to predict future trends. By the end of the reprint, you will be able to use data science to help tourism businesses make better use of data and improve their decision making and operations.

A lisbon case study

Manzolli, J. A., Oliveira, A., & Neto, M. D. C. (2021). Evaluating walkability through a multi-criteria decision analysis approach: A lisbon case study. Sustainability (Switzerland), 13(3), 1-20. [1450]. https://doi.org/10.3390/su13031450New strategies to improve the quality of urban pedestrian environments are becoming increasingly important in sustainable city planning. This trend has been driven by the advantages that active mobility provides in terms of health, social, and environmental aspects. Our work explores the idea of walkability. This concept refers to the friendliness of the urban environment to pedestrian traffic. We propose a framework based on the multi-criteria decision analysis (MCDA) methodology to rank streets in terms of walkability levels. The city of Lisbon (Portugal) is the location of the streets under examination. Findings confirmed the framework’s replicability and suggested the possibility of this strategy being used as a support tool for designing urban policies.publishersversionpublishe

Showcasing New Tourism Destination by Using Gis: a Study of Sikkim

Purpose: The main purpose of this research is to find out new tourist destinations and suggest developmental strategies through scientific ways for solving overtourism-related problems.   Theoretical framework: In this research paper, the researchers emphasized finding new tourist spots and analyzing their potential both in touristic and infrastructural value was assessed by the researcher with the help of a most modern tool like Geographic Information System. The researchers have explained a scientific process of exploring new tourist destinations or tourist spots by using GIS and have shown how to develop proper infrastructure around those spots.   Design/methodology/approach: A “Multicriteria Spatial Decision Support System modeling” was used to find out and validate the existing and new tourist spots. In the pair-wise comparison method, a criterion versus criteria was created to compare each pair of criteria and assign relative ratings using the scale of pair-wise comparison. In this research, the Simple Additive Weighting (SAW) method is used because it gives the “most acceptable results for majority of single-dimensional problems”. The researcher has created this map to support the ‘Destination Fetching Model’, and it can also be used for promoting sustainable tourism in the area. If the entire land cover is visible to the planners with an aerial view, they can plan for tourism infrastructure and superstructures from anywhere. GIS-based layer data has created an "all covered" aerial map with the help of advanced GIS technology, which not helped the planners to understand the current land condition, but also showed the open area which can be utilized for new tourism set-up. Manmade and natural resources are also classified through this LULC model.   Findings: These new tourist spots will help planners and stakeholders to distribute excessive crowds to comparatively new destinations. It is observed that most of the Indian tourism destinations suffer from “over Tourism” in peak season. This research will help spread the flow of tourists to the nearest newly added destinations.   Research, Practical & Social implications: Scientific tourism planning through GIS will also help tourism service providers and planners to add infrastructure to the new destinations, and would also help local people to generate income through tourism. Originality/value: This research will solve the “over tourism” problem of any destination or state, and help generate more visitor’s day at the destination which is proportionate to extra revenue generation for the local, regional and national tourism stakeholders

The Mediating Role of Real-Time Information Between Location-Based User-Generated Content and Tourist Gift Purchase Intention

The global use of Web 2.0 applications has generated enormous volumes of user content. Drawing on cognitive load theory, this study examines unexplored factors that influence gift purchase intention of tourists. The authors identify localization and realtime information for shaping tourists' gift purchase intention, which is facilitated by reduced cognitive overload. Analyzes of the study relies on a sample of 273 foreign tourists in Malaysia. A cross-sectional quantitative study is conducted using partial least square structural equation modeling. Results showed that location-based user-generated content and real-time information significantly affect gift purchase intention of tourists. Moreover, real-time information partially mediates the relationship between location-based user-generated content and gift purchase intention

A Design Concept for a Tourism Recommender System for Regional Development

Despite of tourism infrastructure and software, the development of tourism is hampered due to the lack of information support, which encapsulates various aspects of travel implementation. This paper highlights a demand for integrating various approaches and methods to develop a universal tourism information recommender system when building individual tourist routes. The study objective is proposing a concept of a universal information recommender system for building a personalized tourist route. The developed design concept for such a system involves a procedure for data collection and preparation for tourism product synthesis; a methodology for tourism product formation according to user preferences; the main stages of this methodology implementation. To collect and store information from real travelers, this paper proposes to use elements of blockchain technology in order to ensure information security. A model that specifies the key elements of a tourist route planning process is presented. This article can serve as a reference and knowledge base for digital business system analysts, system designers, and digital tourism business implementers for better digital business system design and implementation in the tourism sector

Towards a Persuasive Recommender for Bike Sharing Systems: A Defeasible Argumentation Approach

[EN] This work proposes a persuasion model based on argumentation theory and users' characteristics for improving the use of resources in bike sharing systems, fostering the use of the bicycles and thus contributing to greater energy sustainability by reducing the use of carbon-based fuels. More specifically, it aims to achieve a balanced network of pick-up and drop-off stations in urban areas with the help of the users, thus reducing the dedicated management trucks that redistribute bikes among stations. The proposal aims to persuade users to choose different routes from the shortest route between a start and an end location. This persuasion is carried out when it is not possible to park the bike in the desired station due to the lack of parking slots, or when the user is highly influenceable. Differently to other works, instead of employing a single criteria to recommend alternative stations, the proposed system can incorporate a variety of criteria. This result is achieved by providing a defeasible logic-based persuasion engine that is capable of aggregating the results from multiple recommendation rules. The proposed framework is showcased with an example scenario of a bike sharing system.This work was supported by the projects TIN2015-65515-C4-1-R and TIN2017-89156-R of the Spanish government, and by the grant program for the recruitment of doctors for the Spanish system of science and technology (PAID-10-14) of the Universitat Politècnica de València.Diez-Alba, C.; Palanca Cámara, J.; Sanchez-Anguix, V.; Heras, S.; Giret Boggino, AS.; Julian Inglada, VJ. (2019). Towards a Persuasive Recommender for Bike Sharing Systems: A Defeasible Argumentation Approach. Energies. 12(4):1-19. https://doi.org/10.3390/en12040662S119124Erdoğan, G., Laporte, G., & Wolfler Calvo, R. (2014). The static bicycle relocation problem with demand intervals. European Journal of Operational Research, 238(2), 451-457. doi:10.1016/j.ejor.2014.04.013Alvarez-Valdes, R., Belenguer, J. M., Benavent, E., Bermudez, J. D., Muñoz, F., Vercher, E., & Verdejo, F. (2016). Optimizing the level of service quality of a bike-sharing system. Omega, 62, 163-175. doi:10.1016/j.omega.2015.09.007Schuijbroek, J., Hampshire, R. C., & van Hoeve, W.-J. (2017). Inventory rebalancing and vehicle routing in bike sharing systems. European Journal of Operational Research, 257(3), 992-1004. doi:10.1016/j.ejor.2016.08.029Li, L., & Shan, M. (2016). Bidirectional Incentive Model for Bicycle Redistribution of a Bicycle Sharing System during Rush Hour. Sustainability, 8(12), 1299. doi:10.3390/su8121299Anagnostopoulou, E., Bothos, E., Magoutas, B., Schrammel, J., & Mentzas, G. (2018). Persuasive Technologies for Sustainable Mobility: State of the Art and Emerging Trends. Sustainability, 10(7), 2128. doi:10.3390/su10072128Galbrun, E., Pelechrinis, K., & Terzi, E. (2016). Urban navigation beyond shortest route: The case of safe paths. Information Systems, 57, 160-171. doi:10.1016/j.is.2015.10.005Ferrara, J. (2013). Games for Persuasion: Argumentation, Procedurality, and the Lie of Gamification. Games and Culture, 8(4), 289-304. doi:10.1177/1555412013496891Fei, X., Shah, N., Verba, N., Chao, K.-M., Sanchez-Anguix, V., Lewandowski, J., … Usman, Z. (2019). CPS data streams analytics based on machine learning for Cloud and Fog Computing: A survey. Future Generation Computer Systems, 90, 435-450. doi:10.1016/j.future.2018.06.042Faed, A., Hussain, O. K., & Chang, E. (2013). A methodology to map customer complaints and measure customer satisfaction and loyalty. Service Oriented Computing and Applications, 8(1), 33-53. doi:10.1007/s11761-013-0142-6Xu, W., Li, Z., Cheng, C., & Zheng, T. (2012). Data mining for unemployment rate prediction using search engine query data. Service Oriented Computing and Applications, 7(1), 33-42. doi:10.1007/s11761-012-0122-2GARCÍA, A. J., & SIMARI, G. R. (2004). Defeasible logic programming: an argumentative approach. Theory and Practice of Logic Programming, 4(1+2), 95-138. doi:10.1017/s147106840300167