Semi-Automated Location Planning for Urban Bike-Sharing Systems

Bike-sharing has developed into an established part of many urban transportation systems. However, new bikesharing systems (BSS) are still built and existing ones are extended. Particularly for large BSS, location planning is complex since factors determining potential usage are manifold. We propose a semi-automatic approach for creating or extending real-world sized BSS during general planning. Our approach optimizes locations such that the number of trips is maximized for a given budget respecting construction as well as operation costs. The approach consists of four steps: (1) collecting and preprocessing required data, (2) estimating a demand model, (3) calculating optimized locations considering estimated redistribution costs, and (4) presenting the solution to the planner in a visualization and planning front end. The full approach was implemented and evaluated positively with BSS and planning experts

Algorithmic approaches for Optimization problems in bike sharing and security control

Most public-bike sharing systems consist of rental stations distributed among a city. These systems are designed for short-term use and single trips, i.e., bikes can be rent and returned at any station in the system. Thus, the problem of rebalancing the system arises, which is denoted as balancing bike sharing system problem. This problem is addressed with various (meta)heuristics and exact methods within this thesis. Moreover, when planning a new system or extending an existing one, the problem of selecting appropriate locations and con gurations for stations arises. Hereby, budget restrictions and other constraints need to be considered and the expected user bene t should be maximized. This problem is referred to as the bike sharing station planning problem. In practice, large instances of this problem must be solved, and it is necessary to come up with a solution method that is able to \overlook the problem as a whole" | classical local-search methods or basic greedy construction methods would not be meaningful. We propose a solution method based on the multilevel re nement paradigm, which utilizes a hierarchically clustered input data. The third combinatorial optimization problem considered in this thesis is the Districting and Routing Problem for Security Control. The optimization goal is to minimize the number of routes that are necessary to perform speci ed visits of buildings. To this end, we propose a smart district elimination algorithm. Lastly, we also study this problem with soft time windows and suggest a fast hybrid heuristic based on dynamic programming, which can frequently yield proven optimal solutions in short times.20

Shared mobility systems: an updated survey

International audienceTransportation habits have been largely modified in the past decade by the introduction of shared mobility systems. These have been a partial response to the need of resorting to green means of transportation and to the desire of being more flexible in the choice of trips, both from a spatial and temporal point of view. On the one hand, shared mobility systems have taken advantage of the interest for shared experiences. On the other hand, their success has been possible as a result of the recent advances in information and communications technology. The operational research community is already very active in this emerging field, which provides a very rich source of new and interesting challenges, covering several planning levels, from strategic to operational ones, such as station location, station sizing, rebalancing routes. A fascinating feature of this field is the variety of the methods used to deal with these questions. Our purpose is to survey the main problems and methods arising in this field. Bicycle and car sharing and Fleet dimensioning and Inventory rebalancing and Shared mobility systems and Survey and Vehicle repositionin