Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries

Gendreau, Michel; Guertin, François; Potvin, Jean-Yves; Séguin, René

doi:10.1016/j.trc.2006.03.002

Cited by 220 publications

(149 citation statements)

References 31 publications

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“…In [36] they proposed a neighborhood search heuristics to optimize the planned routes of vehicles in a context where new requests, with a pick-up and a delivery locatio r programm oposed by them is based on the ej nal experiments show the proposed parallel ro e windows and split delive -heuristics for the large VRPTW instances are based on some form of parallel ey were the first to apply a gen, occur in real-time. This is a dynamic vehicle routing problem (DVRP).…”

Section: Heuristic Approachesmentioning

confidence: 99%

A Survey on the Vehicle Routing Problem and Its Variants

Kumar¹,

Panneerselvam²

2012

IIM

246

126

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In this paper, we have conducted a literature review on the recent developments and publications involving the vehicle routing problem and its variants, namely vehicle routing problem with time windows (VRPTW) and the capacitated vehicle routing problem (CVRP) and also their variants. The VRP is classified as an NP-hard problem. Hence, the use of exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. The vehicle routing problem comes under combinatorial problem. Hence, to get solutions in determining routes which are realistic and very close to the optimal solution, we use heuristics and meta-heuristics. In this paper we discuss the various exact methods and the heuristics and meta-heuristics used to solve the VRP and its variants.

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Section: Heuristic Approachesmentioning

confidence: 99%

A Survey on the Vehicle Routing Problem and Its Variants

Kumar¹,

Panneerselvam²

2012

IIM

246

126

View full text Add to dashboard Cite

show abstract

“…Bent and Hentenryck (2006), Gendreau et al (1998a), Nanry and Barnes (2000), and Ropke and Pisinger (2006). To group together similar requests, the level of attraction between two requests is measured by the proximity between their pickup and delivery locations.…”

Section: Neighborhoodsmentioning

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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“…The problem arises naturally from a broad spectrum of real-world applications, including courier routing [9,15], service scheduling [3,4], Dial-a-Ride systems [2,8,26,27], etc. Depending on which element or elements of the problem become dynamic, numerous variations of the DVRP exist.…”

Section: Literature Reviewmentioning

confidence: 99%

A look-ahead partial routing framework for the stochastic and dynamic vehicle routing problem

Zou

Dessouky

2018

J Veh Routing Algorithms

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In this paper, we study the vehicle routing problem with dynamic customers, where a portion of the customer requests are known in advance and the rest arrive in real time. We propose an optimization-based look-ahead dynamic routing framework that involves request forecasting, partial planning, and dynamic real-time routing of the fleet. This framework has the capabilities for adjustments in response to routing environments with different levels of uncertainties. Through extensive numeral simulations, we exam its performance in routing environments with various levels of uncertainties. We demonstrate the efficiency and robustness of the proposed solution by benchmarking against two other routing strategies. This paper fills the gap in the literature on studying the relationship between the level of route planning in the solution approach and the quality of the solution under various system conditions.

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Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries

Cited by 220 publications

References 31 publications

A Survey on the Vehicle Routing Problem and Its Variants

A Survey on the Vehicle Routing Problem and Its Variants

Dynamic transportation of patients in hospitals

A look-ahead partial routing framework for the stochastic and dynamic vehicle routing problem

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