New Heuristics for the Vehicle Routing Problem

Cordeau, Jean‐François; Gendreau, Michel; Hertz, Alain; Laporte, Gilbert

doi:10.1007/0-387-24977-x_9

Cited by 149 publications

(118 citation statements)

References 50 publications

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“…It started with the seminal papers of [1,2]. Now, VRP offers a wealth of heuristic and metaheuristic approaches, which are surveyed in the papers of [3][4][5]. The VRP is so widely studied because of its wide applicability and its importance in determining efficient strategies for reducing operational costs in distribution networks.…”

Section: Introductionmentioning

confidence: 99%

A Survey on the Vehicle Routing Problem and Its Variants

Kumar¹,

Panneerselvam²

2012

IIM

243

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: Introductionmentioning

confidence: 99%

A Survey on the Vehicle Routing Problem and Its Variants

Kumar¹,

Panneerselvam²

2012

IIM

243

126

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“…However, the situation is totally recovered using the extended support as defined above. Indeed, the percentage value 56.873 improves to 58.793, and the average size of the support does not increase much (from 50.268% to 53.529%). The only large increase in the size of the CGLP arises for problem rout, which is in fact a very instructive case: the "Classical" SNC closed 24.26% of the gap, the "No redundancy" SNC version on the support closes only 6.56%, while in the extended support the situation is totally recovered (and improved) with 30.88% gap closed.…”

Section: Working On the Supportmentioning

confidence: 92%

“…Heuristic and metaheuristic algorithms usually take into account both capacity and distance constraints, and often consider the number of routes as a decision variable. For a comprehensive survey on solution techniques for the Vehicle Routing Problem we refer the reader to [55,56,96,168]. Recent In this chapter we present an Integer Linear Programming (ILP) Local Search algorithm for VRP, based on an exponential neighborhood which is explored by solving an ILP formulation.…”

Section: Introductionmentioning

confidence: 99%

Enhanced mixed integer programming techniques and routing problems

Tramontani

2010

4OR-Q J Oper Res

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“…The problem considered in this paper is a generalisation of the Vehicle Routing Problem (VRP) and the Pickup and Delivery Problem (PDP), see Cordeau et al (2004), Mitrović-Minić (1998) and secondary literature given there. The most widely studied vehicle routing problems are the capacitated VRP and the Vehicle Routing Problem with Time Windows (VRPTW) which are surveyed by Semet (2002), andCordeau et al (2002).…”

Section: Related Workmentioning

confidence: 99%

A General Vehicle Routing Problem

Goel¹,

Gruhn²

2008

European Journal of Operational Research

113

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In this paper, we study a rich vehicle routing problem incorporating various complexities found in real-life applications. The General Vehicle Routing Problem (GVRP) is a combined load acceptance and generalised vehicle routing problem. Among the real-life requirements are time window restrictions, a heterogeneous vehicle fleet with different travel times, travel costs and capacity, multi-dimensional capacity constraints, order/vehicle compatibility constraints, orders with multiple pickup, delivery and service locations, different start and end locations for vehicles, and route restrictions for vehicles. The GVRP is highly constrained and the search space is likely to contain many solutions such that it is impossible to go from one solution to another using a single neighbourhood structure. Therefore, we propose iterative improvement approaches based on the idea of changing the neighbourhood structure during the search.

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New Heuristics for the Vehicle Routing Problem

Cited by 149 publications

References 50 publications

A Survey on the Vehicle Routing Problem and Its Variants

A Survey on the Vehicle Routing Problem and Its Variants

Enhanced mixed integer programming techniques and routing problems

A General Vehicle Routing Problem

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