Interactive Approaches for Sightseeing Route Planning under Uncertain Traffic and Ambiguous Tourist's Satisfaction

Interactive Approaches for Sightseeing Route Planning under Uncertain Traffic and Ambiguous Tourist's Satisfaction

Takashi Hasuike (Osaka University, Japan), Hideki Katagiri (Hiroshima University, Japan), Hiroe Tsubaki (The Institute of Statistical Mathematics, Japan) and Hiroshi Tsuda (Doshisha University, Japan)
Copyright: © 2015 |Pages: 22
DOI: 10.4018/978-1-4666-8577-2.ch005


This paper proposes an interactive approach to obtain an appropriate sightseeing route for the tourist under various uncertain traffic and climate conditions including time-dependent parameters and ambiguous satisfaction values at sightseeing sites. Since the uncertain traffic and climate conditions include time-dependent conditions, Time Expanded Network (TEN) are proposed for each condition. Furthermore, interval numbers for ambiguous satisfaction values are proposed, and hence, the proposed model is formulated as a multiobjective interval programming problem with many constraints derived from network optimization. In order to transform the multiobjective into the single-objective, Minkowski's Lp-metric is introduced as a compromise approach. From the final formulation of our proposed model using the optimistic satisfactory for interval numbers, an interactive algorithm to obtain the appropriate sightseeing route communicating with the tourist is developed.
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Information and communication technologies (ICT) including internet technologies are rapidly developed in recent years, and the ICT enables tourists to use a wide variety of information and to do personalized sightseeing planning themselves on the Web. Therefore, it is important in developing decision support for sightseeing route planning under various traffic and weather conditions. Furthermore, travel and activity times are also important factors for sightseeing, and hence, it is necessary to suitably manage them for effective sightseeing activities. The route planning is a multimodal constructive activity under some features, which can be classified into several categories (Zhu et al., 2012); (1) personal socioeconomic and psychological features based on age, education, income, experience, personality, and involvement, (2) travel features such as travel purpose, number of travelers, length of travel, and distance, (3) other features for suitable management considering traveling and sightseeing times. Thus, the sightseeing route planning in network optimization should be prepared in advance, considering the above-mentioned features and parameters such as transportations, personal context, properties of activities, and times.

Previous researches of sightseeing route planning are broadly divided into several groups (Abbaspour & Samadzadegan, 2011). Particularly, this study is focused on the mathematical point of view. Previous mathematical models for sightseeing route planning did not include several important factors such as uncertainty of required travel times and ambiguity of satisfaction values at sightseeing sites. In terms of uncertainty of required travel times, historical traffic data suggests that tourists may estimate travel time between two sightseeing sites. However, the actual travel time is different from the prediction, and hence, it is not appropriate to set each travel time as a constant, i.e., we need to consider uncertainty in a given traffic network. Furthermore, weather and climate conditions are also important to travel time and satisfactions at sightseeing sites. For instance, a zoo is largely outdoors, making it a weather-dependent location. On the other hand, an aquarium is a weather-independent location, because the activities are mostly indoors. Therefore, the satisfaction value at a zoo changes more dramatically than that of an aquarium due to the weather conditions.

Thus, it is important to consider the time-dependent (or weather-dependent) parameters in sightseeing route planning, but previous mathematical models of sightseeing route planning did not include the time-dependency of both traveling times and satisfaction values, simultaneously. Particularly, it is generally difficult to represent these necessary conditions using only one static network structure not including the time-expansion, because static network optimization problems give only one deterministic value to each edge. In this study, we introduce a network structure called Time-Expanded Network (TEN) (or Time-Space Network (TSN)) to deal with time-dependent parameters in our proposed model. As mentions in some papers (for instance, (Hasuike et al., 2013A; 2013B; 2014A; 2014B)), the advantage is to represent an optimal flow over time as a standard static network flow problem on the TEN. Therefore, many researchers have applied the TEN to practical problems until now (Chu et al., 2012; Engineer et al, 2011; Guo et al., 2006; Hane et al., 1995; Kliewer et al., 2006; Shah et al., 2012; Yan & Chen, 2011; Zawack & Gerald, 1987). In this paper, we focus on the modeling of sightseeing route planning considering several time-dependent factors for times and satisfactions and applying the usefulness of TEN to our proposed tour planning problem.

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