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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
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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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Applying GIS and Or Techniques to Solve Sears Technician-Dispatching and Home Delivery Problems

Don Weigel, +1 more
- 01 Jan 1999 - 
TL;DR: A series of algorithms are constructed, including the algorithm to build the origin-and-destination matrix, the algorithms to assign resources, and algorithms to perform sequencing and route improvement for the Sears technician-dispatching and home-delivery business.
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Local Search for Vehicle Routing and Scheduling Problems: Review and Conceptual Integration

TL;DR: This paper provides a review of both classical and modern local search neighborhoods for this class of problems and shows how the properties of the partial moves and the constraints of the VRSP influences the choice of an appropriate search technique.
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Optimal liner fleet routeing strategies.

TL;DR: Two optimization models that can be useful to liner shipping companies are suggested, one is a linear programming model of profit maximization, which provides an optimal routing mix for each ship available and optimal service frequencies for each candidate route, and the other is a mixed integer programming model with binary variables which provides optimal routing mixes and service frequencies.
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Parallel Savings Based Heuristics for the Delivery Problem

TL;DR: In this paper, the authors presented parallel savings algorithms PSAs for generating feasible solutions to the delivery problem, which combines the savings approach, with matching based procedures, and showed that the average quality of solutions generated by PSAs is significantly superior on large sets of test problems.

Parallelization of the Vehicle Routing Problem with Time Windows

Jesper Larsen
TL;DR: A parallel algorithm based on the sequential algorithm developed in the previous part of the dissertation is developed and analyzed and a number of techniques to improve the performance of the column-generation framework are proposed and analyzed.