Tourist trip planning functionalities : state-of-the-art and future

When tourists visit a city or region, they cannot visit every point of interest available, as they are constrained in time and budget. Tourist recommender applications help tourists by presenting a personal selection. Providing adequate tour scheduling support for these kinds of applications is a daunting task for the application developer. The objective of this paper is to demonstrate how existing models from the field of Operations Research (OR) fit this scheduling problem, and enable a wide range of tourist trip planning functionalities. Using the Orienteering Problem (OP) and its extensions to model the tourist trip planning problem, allows to deal with a vast number of practical planning problems

Generating Travel Itinerary Using Ant Collony Optimization

Travelling is one of the activities needed by everyone to overcome weariness. The number of information about the tourism destination on the internet sometimes does not provide easiness for oncoming tourists. This paper proposes a system capable of making travel itinerary, for tourists who want to visit an area within a few days. For generating itinerary, the system considers several criterias (Multi-criteria-based), which include the popularity level of tourist attractions to visit, tourist visits that minimize budgets or tourist visits with as many destinations as possible. To handle multi criteria-based itinerary, we use the concept of multi attribute utility theory (MAUT). The running time of multi criteria-based itinerary is not significantly different from time-based itinerary. In addition, the number of tourist attractions in the itinerary is more than time-based itinerary, because the combination of solutions from each ant becomes more diverse

Travel route scheduling based on user’s preferences using simulated annealing

Nowadays, traveling has become a routine activity for many people, so that many researchers have developed studies in the tourism domain, especially for the determination of tourist routes. Based on prior work, the problem of determining travel route is analogous to finding the solution for travelling salesman problem (TSP). However, the majority of works only dealt with generating the travel route within one day and also did not take into account several user’s preference criteria. This paper proposes a model for generating a travel route schedule within a few days, and considers some user needs criteria, so that the determination of a travel route can be considered as a multi-criteria issue. The travel route is generated based on several constraints, such as travel time limits per day, opening/closing hours and the average length of visit for each tourist destination. We use simulated annealing method to generate the optimum travel route. Based on evaluation result, the optimality of the travel route generated by the system is not significantly different with ant colony result. However, our model is far more superior in running time compared to Ant Colony method

A Semantic Social Recommender System Using Ontologies Based Approach For Tunisian Tourism

Tunisia is well placed in terms of medical tourism and has highly qualified and specialized medical and surgical teams. Integrating social networks in Tunisian medical tourism recommender systems can result in much more accurate recommendations. That is to say, information, interests, and recommendations retrieved from social networks can improve the prediction accuracy. This paper aims to improve traditional recommender systems by incorporating information in social network; including user preferences and influences from social friends. Accordingly, a user interest ontology is developed to make personalized recommendations out of such information. In this paper, we present a semantic social recommender system employing a user interest ontology and a Tunisian Medical Tourism ontology. Our system can improve the quality of recommendation for Tunisian tourism domain. Finally, our social recommendation algorithm is implemented in order to be used in a Tunisia tourism Website to assist users interested in visiting Tunisia for medical purposes

TIME-DEPENDENT THEME PARK ROUTING PROBLEM BY PARTHENO-GENETIC ALGORITHM

As the remarkable improvement of people\u27s living levels and interesting for entertainment, the theme park has become one of the most popular places for people to enjoy life. However, since the high popularity of theme parks, based on the reality circumstance of tourists, enjoying more attraction projects and decreasing the fatigue greatly can largely improve the satisfaction of tourists. Therefore, based on the network of Traveling Salesman Problem (TSP), we propose a time-dependent theme park routing problem where the walking time is time-dependent under the consideration of congestion and fatigue degree. The primary objectives are to maximize the number of visited attractions, satisfaction and minimize the queuing time and walking time. In this study, the general model for time-dependent theme park problem is formulated and two different algorithms are used to solve the model. The numerical experiments are conducted to verify the feasibility and effectiveness

Development of a tourism recommender system

Nowadays, many people rely on online services to plan a trip. However, they are usually faced with the problem of being supplied with lots of information. In consequence, they have to invest a great deal of time to decide what to visit, when, etc. This huge amount of possibilities available on the net makes it difficult for users to discern the more interesting offers from the rest. As a result, the more appealing offers can go unnoticed. In order to improve the tourist experience, recommender systems offer personalised information to users. In other words, the system selects the more suitable and adequate offers for users and offers activities appropriate to their profile. In this thesis, we present the EnoSigTur system, a smart recommender system for tourists interested in experiences related to the wine sector. It has been developed in the Parc Científic i Tecnològic de Turisme i Oci of Vila-seca with the collaboration of researchers in the Universitat Rovira i Virgili. Trough a web application, the system allows users to know wine production activities available in the region of Tarragona. Users just have to indicate their interests in general terms and the system will select the more convenient activities for them. EnoSigTur is capable of modifying the initial information of the users preferences by studying the interaction between the user and the system, and offering them more adjusted recommendations. This system also allows users to plan a trip by providing advanced planning services; for example, date, length of the trip, etc. A mobile phone application will permit users to monitor the planned trip while it is taking place. EnoSigTur is designed to supply a user-friendly and flexible service either to visitors with a superficial knowledge of the wine production area, or to experienced visitors who have already been in contact with these types of activities. Moreover, as we suggested before, it provides personalised recommendations according to users interests, gives clients the necessary tools to plan the trip and makes it possible for them to discover other activities in the region. In the following chapters we will deal with the main problems that tourism presents in terms of information search and decision-making processes. We will also present the recommender systems and the ontology, so that the reader will be able to grasp the gist of the project. Finally, we will give details of our recommender system

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