A multi-criteria route planning model based on fuzzy preference degrees of stops

Abstract

Integrated utilization of new technologies such as smart phones, tablet devices, and satellite maps has entered our daily lives recently. Nevertheless, many new applications are being developed mostly based on these technologies. The optimal route planning, which makes use of the public transport network structure between any selected origin and destination points, is one of the interesting applications among them. Route planning applications used today mostly focus on the aspects such that passengers use nearest stops around origin and destination geographical points, or use set of stops around these points within some walking radius. In these applications, which work on the classical (crisp) logic base, all stops on the walking distance have the same preference degree. However, in this study a novel fuzzy model is proposed which also takes into account preferences such as the stop’s activity, and count of transit lines passing through the stop besides the walking distance. Using all these three preferences, aggregated fuzzy preference degrees of stops are calculated. The “optimum” routes between any origin and destination pair are constructed using feasible transfer points, which are chosen among the alternatives having the highest preference degrees overall. Fuzzy neighborhood relations such as “stop-stop”, “stop-line”, and “line-line” are introduced in order to employ in preference degree evaluations.Apart from the aggregated degree of the preferences mentioned above, we also consider to minimize the total number of transit stops travelled on any route for establishing optimal routes. This additional preference can be described the time duration spent on transport vehicles, such as buses, trains, subways or ferries. Therefore, we propose a two-criteria route-planning problem in this study, where we try to maximize the aggregated preference degree of a route and to minimize the number of stops used on a route. Fuzzy optimal solutions for this problem are constructed via γ-level solutions of the fuzzy problem and a heuristic algorithm providing these solutions is proposed. This model and its algorithm can be considered as an optimal route search engine for mobile applications that could be used by urban public transport passengers.