A tabu search heuristic for the dynamic transportation of patients between care units

Kergosien, Yannick; Lenté, Christophe; Piton, D.; Billaut, Jean‐Charles

doi:10.1016/j.ejor.2011.04.033

Cited by 58 publications

(44 citation statements)

References 31 publications

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“…Depending on the medical procedure or facility capacity, a patient may need to be transferred on short notice from one service to another, possibly requiring trained staff or specific equipment for his/her care. This application has been studied by Beaudry et al [7], Kergosien et al [80], and Melachrinoudis et al [96].…”

Section: Transport Of Personsmentioning

confidence: 99%

A review of dynamic vehicle routing problems

Pillac

Gendreau

Guéret

et al. 2013

European Journal of Operational Research

964

496

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A number of technological advances have led to a renewed interest on dynamic vehicle routing problems. This survey classifies routing problems from the perspective of information quality and evolution. After presenting a general description of dynamic routing, we introduce the notion of degree of dynamism, and present a comprehensive review of applications and solution methods for dynamic vehicle routing problems.

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Section: Transport Of Personsmentioning

confidence: 99%

A review of dynamic vehicle routing problems

Pillac

Gendreau

Guéret

et al. 2013

European Journal of Operational Research

964

496

View full text Add to dashboard Cite

show abstract

“…A DARP with heterogeneous users and vehicles is studied in [24] where different modes (seated, stretcher and wheelchair) and types of vehicles are considered. The problem studied in [21] was inspired by a real case of transportation of patients in a hospital complex in France, where transportations are subject to particular constraints. Among them, its worth to mention priority of urgent demands, disinfection of a vehicle after the transportation of a contagion, respect of the type of vehicle needed and the opportunity to outsource demands to a private company.…”

Section: Literature Reviewmentioning

confidence: 99%

Managing a Fleet of Ambulances to Respond to Emergency and Transfer Patient Transportation Demands

Kergosien

Gendreau

Ruiz

et al. 2013

Springer Proceedings in Mathematics &Amp; Statistics

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Organizations of pre-hospital emergency medical services have as first mission to provide medical assistance to patients including transport to medical centers if necessary, and a second one that concerns the transfers of patients from one medical facility to another one. Most organizations in Canada and in North-America use two independent fleets to perform these missions. Although operating two separated fleets seems easier to do, it appears to be less efficient than an integrated fleet management approach able to deal with both types of demands. Taking this into consideration, this paper aims to design and evaluate the performance of three management approaches. This is a very challenging problem, since it involves solving simultaneously two difficult vehicle routing problems: an ambulance relocation problem and a dial a ride problem.

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“…This directly leads to the goal of minimising the strategy's performance metrics related to "sojourn time" (including EV's travel time, waiting time for charging, and charging time), which is different from the well-known Vehicle Routing Problem (VRP) (Dantzig & Ramser, 1959;Pillac, Gendreau, Guéret, & Medaglia, 2013) and Dynamic Traveling Repairman Problem (DTRP) (Bertsimas & Ryzin, 1990, 1993 that involve design of vehicledelivery routes from a depot to a set of scattered demand locations, so as to minimise the overall routing cost (e.g., travel time/distance) under various side constraints (Baldacci, Toth, & Vigo, 2007;Ferrucci, Block, & Gendreau, 2013;Jaillet & Wagner, 2008;Kergosien, Lenté, Piton, & Billaut, 2011;Laporte, 2007Laporte, , 2009Li, Mirchandani, & Borenstein, 2009;Pavone, Frazzoli, & Bullo, 2007;Pillac et al, 2013;Solomon, 1987). We assume that service demands are placed by the EV drivers according to a general process, and the distribution of the locations of where EVs originate is arbitrary, although its support is determined by a compact Euclidean service region.…”

Section: Introductionmentioning

confidence: 99%