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Routing and scheduling of vehicles and crews–the state of the art

L. Bodin
- 01 Jan 1983 - 
- Vol. 10, Iss: 2, pp 69-211
About: 
This article is published in Computers & Operations Research.The article was published on 1983-01-01 and is currently open access. It has received 1046 citations till now. The article focuses on the topics: Static routing & Policy-based routing.

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A parallel implementation of the tabu search heuristic for vehicle routing problems with time window constraints

Bruno-Laurent Garcia, +2 more
- 01 Nov 1994 - 
TL;DR: A parallel Tabu search heuristic for the Vehicle Routing Problem with Time Windows, which is synchronous and runs on a Multiple-Instruction Multiple-Data computer architecture.
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Models and Algorithms for Integration of Vehicle and Crew Scheduling

Richard Freling, +2 more
- 01 Jan 2003 - 
TL;DR: This paper deals with models, relaxations, and algorithms for an integrated approach to vehicle and crew scheduling for an urban mass transit system with a single depot, and proposes new mathematical formulations for integrated vehicle andCrew scheduling problems and corresponding Lagrangian relaxations and Lagrangia heuristics.
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Fuzzy vehicle routing model with credibility measure and its hybrid intelligent algorithm

Yongshuang Zheng, +1 more
- 15 May 2006 - 
TL;DR: F fuzzy simulation and genetic algorithm are integrated to design a hybrid intelligent algorithm to solve the fuzzy vehicle routing model in which the travel times are assumed to be fuzzy variables.
Journal ArticleDOI

On optimal trees

Peter Eades, +1 more
- 01 Dec 1981 - 
TL;DR: There are regular trees (as defined in the paper) which are nearly optimal among trees with a given number of nodes, and that minimal-cost trees are often nearly regular.
Journal ArticleDOI

A Branch-and-Cut Procedure for the Vehicle Routing Problem with Time Windows

Jonathan F. Bard, +2 more
- 01 May 2002 - 
TL;DR: A wide variety of cuts is introduced to tighten the linear programming (LP) relaxation of the original mixed-integer program and ever increasing lower bounds on the optimal solution are obtained by solving a series of relaxed problems that incorporate newly found valid inequalities.