دانلود مقاله ISI انگلیسی شماره 93115
ترجمه فارسی عنوان مقاله

یک الگوریتم اکتشافی برای یک دوچرخه متحرک استاتیک یک مشکل تعادل متعادل است

عنوان انگلیسی
A heuristic algorithm for a single vehicle static bike sharing rebalancing problem
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
93115 2017 33 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Computers & Operations Research, Volume 79, March 2017, Pages 19-33

ترجمه کلمات کلیدی
اشتراک دوچرخه، مسیریابی خودرو، تقسیم وانت و تحویل، جستجو محلی،
کلمات کلیدی انگلیسی
Bike-sharing; Vehicle routing; Split pickup and delivery; Iterated local search;
پیش نمایش مقاله
پیش نمایش مقاله  یک الگوریتم اکتشافی برای یک دوچرخه متحرک استاتیک یک مشکل تعادل متعادل است

چکیده انگلیسی

The static bike rebalancing problem (SBRP) concerns the task of repositioning bikes among stations in self-service bike-sharing systems. This problem can be seen as a variant of the one-commodity pickup and delivery vehicle routing problem, where multiple visits are allowed to be performed at each station, i.e., the demand of a station is allowed to be split. Moreover, a vehicle may temporarily drop its load at a station, leaving it in excess or, alternatively, collect more bikes from a station (even all of them), thus leaving it in default. Both cases require further visits in order to meet the actual demands of such station. This paper deals with a particular case of the SBRP, in which only a single vehicle is available and the objective is to find a least-cost route that meets the demand of all stations and does not violate the minimum (zero) and maximum (vehicle capacity) load limits along the tour. Therefore, the number of bikes to be collected or delivered at each station must be appropriately determined in order to respect such constraints. We propose an iterated local search (ILS) based heuristic to solve the problem. The ILS algorithm was tested on 980 benchmark instances from the literature and the results obtained are competitive when compared to other existing methods. Moreover, our heuristic was capable of finding most of the known optimal solutions and also of improving the results on a number of open instances.