Disposition and Site Selection Optimization of Rental Bicycle System

• Main Authors: FANG-RUI XIE, 謝昉叡
• Other Authors: Shang-Yao Yan
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/99988076939692527260

碩士 === 國立中央大學 === 土木工程研究所 === 99 === Recent years, more and more people are caring about environment protection. Therefore, it brings the concept of the “Sustainable Transport” to our life. For encouraging people to lower our carbon footprint, conserve energy, and accomplish the goal of sustainable development, there are many rental bicycle services being developed. However, currently in Taiwan, rental bicycle service schedules still planed by the decision center staffs with experience. Without a systematic optimization analysis, and often result in waste resourses. While facing with more complicated problem like “rent bicycle at A station, and return it at B station”, such a manual approach is considered to be less than efficient, and may possibly result in an inferior feasible solution. As a result, focusing on “rent and return bicycle at the same station”and“rent bicycle at A station, and return it at B station”, we constructed some sure and stochastic rental bicycle models that considers the influence of sure and stochastic demand. The matching model is expected to be an effective tool for the planner to solve rental bicycle disposition and site selection problems. Moreover, little literature that proposed effective models for solving problems which relate with rental bicycle system disposition. Therefore, in this study we put ourselves in rental bicycle station proprietor position, consider operation goals in reality and constraint conditions, and employ time-space network techniques, according to different circumstances to construct some rental bicycle models. All decision models are formulated as an integer multiple problem and is solved using a mathematical programming solver. To evaluate models in practice we performed a case study based on the operating data from Taipei public rental bicycle system. The results show the model could be useful. Finally, conclusions and suggestions are given