دانلود رایگان مقاله مدل برنامه ریزی مسیر چند معیاره بر اساس ایستگاه های درجه اولویت فازی

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.

6. Conclusion One ofthe basic concepts used in the literature concerning route planning is the walking distance of a person. Walking distance is known to be an important criterion in trip planning problem, but in real life situations it is not sufficient to determine which stop is the most suitable one. In this paper, we introduce two new criteria such as stop activity and being hub stop besides this criterion, and they are evaluated together by using fuzzy logic, where these three criteria constitute the fuzzy preference degree of any stop. It should be noted that, in order to determine fuzzy preference degree of a stop in other real life applications, more criteria will also have to be incorporated in our problem. For instance, railway and ferry transportation might be more preferable than bus trips, since these transportation types and their routes are not directly affected by road traffic. Although people sometimes need to walk a long distance for reaching at a metro station or a pier, they might still prefer these transportation modes rather than walking to a bus station within a shorter distance. For this reason, the type of the stop/station such as bus stop, metro station, railway station and pier can be added as a new criterion for future studies. Other possible criteria regarding our problem might be considered as well, however, since we focus on demonstrating a fuzzy multi-criteria optimization approach in this study, this is left as another study topic for the future. Finally, we can conclude that the fuzzy multi-criteria route planning model proposed in this study, which handles preference degrees of the stops, is a new approach to route planning problems based on fuzzy logic. The preference degrees are built on fuzzy neighborhood relations among stops, lines and between lines and stops. The proposed model can be employed to a search engine in optimal route planning applications for public transport users, to handle fuzzy human preferences more adequately.