Balancing the stations of a self service “bike hire” system

Benchimol, Mike; Benchimol, Pascal; Chappert, Benoît; Taille, Arnaud de la; Laroche, Fabien; Meunier, Frédéric; Robinet, Ludovic

doi:10.1051/ro/2011102

Cited by 212 publications

(90 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Chemla et al (2012) present a branch-and-cut algorithm for the single-vehicle problem, with results on instances of up to 100 stations. Approximation algorithms for the same problem are given by Benchimol et al (2011). The work of Contardo et al (2012) can be considered state of the art for the multi-vehicle target inventory problem, using Dantzig-Wolfe and Benders decomposition to derive lower bounds and feasible solutions with low computing times (approximately 5 minutes) for instances of 5 vehicles and up to 100 stations.…”

Section: Related Workmentioning

confidence: 99%

Inventory rebalancing and vehicle routing in bike sharing systems

Schuijbroek

Hampshire

Hoeve

2017

European Journal of Operational Research

467

304

View full text Add to dashboard Cite

Bike sharing systems have been installed in many cities around the world and are increasing in popularity. A major operational cost driver in these systems is rebalancing the bikes over time such that the appropriate number of bikes and open docks are available to users. We combine two aspects that have previously been handled separately in the literature: determining service level requirements at each bike sharing station, and designing (near-)optimal vehicle routes to rebalance the inventory. Since finding provably optimal solutions is practically intractable, we propose a new cluster-first route-second heuristic, in which the polynomialsize Clustering Problem simultaneously considers the service level feasibility constraints and approximate routing costs. Extensive computational results on real-world data from Hubway (Boston, MA) and Capital Bikeshare (Washington, DC) are provided, which show that our heuristic outperforms a pure mixed integer programming formulation and a constraint programming approach.

show abstract

Section: Related Workmentioning

confidence: 99%

Inventory rebalancing and vehicle routing in bike sharing systems

Schuijbroek

Hampshire

Hoeve

2017

European Journal of Operational Research

467

304

View full text Add to dashboard Cite

show abstract

“…Among them, the most eye-catching research direction is the repositioning of bicycles, and this area harvested a wealth of research results. Benchimol et al [7] first provided the bicycle-repositioning problem (BRP) and presented a method to deal with the balancing of the stations when no bikes are moving. Forma et al [8] classified the BRP as a variation of the Pickup and Delivery Problem (PDP).…”

Section: Literature Reviewmentioning

confidence: 99%

A Dynamic Programming Model for Operation Decision-Making in Bicycle Sharing Systems under a Sustainable Development Perspective

Shan

Liu

et al. 2017

Sustainability

View full text Add to dashboard Cite

Abstract:Maintaining a balance between revenue and expenditure is the key to the sustainable development of a bicycle sharing system (BSS), and is a challenge for almost all systems worldwide. This article proposes a dynamic programming approach to obtain the optimal strategy to maximize the revenue of overall BSS. The Variable Granularity-Depth First Search (VG-DFS) algorithm is designed to speed up the solution. A numerical experiment is presented to verify the applicability of the model through a comparison with real data from the BSS in Hangzhou. Results indicated that the BSS could achieve break-even, or even obtain a substantial income by utilizing our model to make operational decisions, especially when the region it is located in has a relatively high GDP. Moreover, the best investment strategy proved is to involve stations in the initial construction period of the BSS as much as possible.

show abstract

“…Their approach is designed for a single vehicle and consists of a branch-and-cut algorithm on a relaxed MIP model in conjunction with a tabu search for the local improvement of solutions. Benchimol et al [1] focus on approximation algorithms for selected special situations. Their approaches also assume balancing as a hard constraint and are limited to a single vehicle.…”

Section: Related Workmentioning

confidence: 99%

A PILOT/VND/GRASP Hybrid for the Static Balancing of Public Bicycle Sharing Systems

Papazek

Raidl

Rainer-Harbach

et al. 2013

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. Due to varying user demands in bicycle sharing systems, operators need to actively shift bikes between stations by a fleet of vehicles. We address the problem of finding efficient vehicle tours by an extended version of an iterated greedy construction heuristic following the concept of the PILOT method and GRASP and applying a variable neighborhood descend (VND) as local improvement. Computational results on benchmark instances derived from the real-world scenario in Vienna with up to 700 stations indicate that our PILOT/GRASP hybrid especially scales significantly better to very large instances than a previously proposed variable neighborhood search (VNS) approach. Applying only one iteration, the PILOT construction heuristic followed by the VND provides good solutions very quickly, which can be potentially useful for urgent requests.

show abstract

Balancing the stations of a self service “bike hire” system

Cited by 212 publications

References 10 publications

Inventory rebalancing and vehicle routing in bike sharing systems

Inventory rebalancing and vehicle routing in bike sharing systems

A Dynamic Programming Model for Operation Decision-Making in Bicycle Sharing Systems under a Sustainable Development Perspective

A PILOT/VND/GRASP Hybrid for the Static Balancing of Public Bicycle Sharing Systems

Contact Info

Product

Resources

About