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With the rapid development of sharing economy, bike-sharing becomes essential because of its zero emission, high flexibility and accessibility. The emergence of the public bicycle system not only alleviates the traffic pressure to a certain extent, but also contributes to solving the “last kilometer” problem of public transportation. However, due to the concentrated use of shared bikes, many shared bikes are left in disorder, which seriously affects the urban environment and causes traffic problems. How to manage the allocation of bike-sharing and improve the city’s shared cycling system have become a highly discussed issue. We, taking Beijing as an example, research on the allocation of shared bikes by using the open source data provided by Amap, Baidu Map and websites of shared bikes, which are used to analyze the allocation, and establish an optimizing comprehensive evaluation model to evaluate the required level. In the end, we look forward the future of bike-sharing market.

One of the most important aspects in the design of multi-robot systems (MRS) is the allocation of tasks among the robots in a productive and efficient manner. This paper presents an empirical study on task allocation strategies in multirobot environment. In general, optimal solutions are found through an exhaustive search, but because there are n × m ways in which m tasks can be assigned to n robots, an exhaustive search is often not possible with increased number of tasks. Task allocation methodologies for multirobot systems are developed by considering their capability in terms of time and space. The present work adopts a two-phase methodology to allocate tasks optimally amongst the candidate robots. The allocation cost of the robots is determined during the first phase and alternate algorithms are used in the second phase for optimizing the allocation. The work considers systems of practical sizes and the results obtained through this are helpful in recommending appropriate techniques to the users of MRS for increasing producibility and robot utilization. Three different approaches using Linear programming, Hungarian Algorithm and Knapsack Algorithm are presented and their results are analyzed for the suitability of the methods for an allocation problem. Simulation results are presented and compared for the benefit of the users.