A two-phase insertion technique of unexpected customers for a dynamic dial-a-ride problem

Coslovich, Luca; Pesenti, Raffaele; Ukovich, Walter

doi:10.1016/j.ejor.2005.02.038

Cited by 118 publications

(61 citation statements)

References 17 publications

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“…Madsen et al (1995) have developed an insertion algorithm inspired by the work of Jaw et al (1986) and have applied it to a real-life dynamic problem with multiple objectives. Recently, Coslovich et al (2006) presented a two-phase insertion algorithm for quickly deciding on the acceptance or rejection of a user request. While it makes sense to run an algorithm for a few hours in a static context, much faster response times are required in a dynamic environment.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic transportation of patients in hospitals

Beaudry¹,

et al. 2008

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This paper analyzes and solves a patient transportation problem arising in several large hospitals. The aim is to provide an efficient and timely transport service to patients between several locations on a hospital campus. Transportation requests arrive in a dynamic fashion and the solution methodology must therefore be capable of quickly inserting new requests in the current vehicle routes. Contrary to standard dial-a-ride problems, the problem under study contains several complicating constraints which are specific to a hospital context. The paper provides a detailed description of the problem and proposes a two-phase heuristic procedure capable of handling its many features. In the first phase a simple insertion scheme is used to generate a feasible solution, which is improved in the second phase with a tabu search algorithm. The heuristic procedure was extensively tested on real data provided by a German hospital. Results show that the algorithm is capable of handling the dynamic aspect of the problem and of providing high quality solutions. In particular, it succeeded in reducing waiting times for patients while using fewer vehicles.

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Section: Literature Reviewmentioning

confidence: 99%

Dynamic transportation of patients in hospitals

Beaudry¹,

et al. 2008

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“…The diversion time or "excess ride time" has been recognised in DARP studies as a key measure of the passenger service level [18,19] and is particularly important in healthcare applications [20]. The PTS routing problem is relatively simple in many respects: the vehicles tend to deliver (or collect on the reverse journey) patients from a single hospital, or at least very similar locations; in comparison the standard DARP vehicle often transports passengers with a great variety of destinations.…”

Section: An Example Of a Dial-a-ride Problemmentioning

confidence: 99%

“…Some studies have examined dynamic variants of DARP using insertion heuristics to accommodate new requests [18,21]. Other studies explore the stochastic nature of demand, typically using simulation [22,23,24,25].…”

Section: Darp and Stochastic Demandmentioning

confidence: 99%

Developing a resource allocation model for the Scottish patient transport service

Bowers

Lyons

Mould

2012

Operations Research for Health Care

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The Patient Transport Service is a vital component of many healthcare systems. However, increasing demand and constrained resources impose great challenges, especially in Scotland where there is a substantial remote and rural population. This case study describes the development of a decision support tool for strategic resource allocation decisions. The tool had to be relevant to management's practical needs including transparency to a range of stakeholders and a flexible speedy response to help management explore various operational and policy options. However, the tool also had to demonstrate rigour and identify an efficient allocation of resources. In response to these requirements, the decision support tool was constructed from simple models, verified in comparisons with more rigorous and sophisticated approaches, notably a Dial-a-Ride genetic algorithm and an open vehicle routing simulation. Using this tool, management were able to: identify a more rational, strategic allocation of resources; quantify the remote and rural effect; examine trade-offs between service level and resource requirements within various scenarios for future demand.

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“…For the static variant, starting from the solution proposed by Jaw et al [29], a great number of heuristics have been developed which are explained in further detail in [16], [17], [25]. The dynamic multi-vehicle DARP was addressed by a smaller number of studies, including the work on heuristics in [30]- [32] where instances of up to a several hundred users could be solved. It, however, needs to be mentioned that most so-called dynamic DARPs are only dynamic in a sense that in addition to a static case a fraction of requests may occur or be canceled during operation time.…”

Section: A General Contextmentioning

confidence: 99%

A Partition-Based Match Making Algorithm for Dynamic Ridesharing

Pelzer¹,

Xiao²,

Zehe³

et al. 2015

IEEE Trans. Intell. Transport. Syst.

112

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Abstract-Ridesharing offers the opportunity to make more efficient use of vehicles while preserving the benefits of individual mobility. Presenting ridesharing as a viable option for commuters, however, requires minimizing certain inconvenience factors. One of these factors includes detours which result from picking up and dropping off additional passengers. This paper proposes a method which aims to best utilize ridesharing potential while keeping detours below a specific limit. The method specifically targets ridesharing systems on a very large scale and with a high degree of dynamics which are difficult to address using classical approaches known from operations research. For this purpose, the road network is divided into distinct partitions which define the search space for ride matches. The size and shape of the partitions depend on the topology of the road network as well as on two free parameters. This allows optimizing the partitioning with regard to sharing potential utilization and inconvenience minimization. Match making is ultimately performed using an agent-based approach. As a case study, the algorithm is applied to investigate the potential for taxi sharing in Singapore. This is done by considering about 110 000 daily trips and allowing up to two sharing partners. The outcome shows that the number of trips could be reduced by 42% resulting in a daily mileage savings of 230 000 km. It is further shown that the presented approach exceeds the mileage savings achieved by a greedy heuristic by 6% while requiring 30% lower computational efforts.

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A two-phase insertion technique of unexpected customers for a dynamic dial-a-ride problem

Cited by 118 publications

References 17 publications

Dynamic transportation of patients in hospitals

Dynamic transportation of patients in hospitals

Developing a resource allocation model for the Scottish patient transport service

A Partition-Based Match Making Algorithm for Dynamic Ridesharing

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