A Branch-and-Price Framework for the Maximum Covering and Patrol Routing Problem

2021 ◽  
pp. 59-80
Author(s):  
Paul A. Chircop ◽  
Timothy J. Surendonk ◽  
Menkes H. L. van den Briel ◽  
Toby Walsh
Keyword(s):  
Branch And Price ◽  
Routing Problem ◽  
Patrol Routing

A branch-and-price approach for the parallel drone scheduling vehicle routing problem

2021 ◽  
Author(s):  
Ritwik Raj ◽  
Dowon Lee ◽  
Seunghan Lee ◽  
Jose Walteros ◽  
Chase Murray
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Branch And Price ◽  
Routing Problem ◽  
Price Approach

A Branch-and-Price Approach to the Vehicle Routing Problem with Simultaneous Distribution and Collection

2006 ◽  
Vol 40 (2) ◽  
pp. 235-247 ◽  
Author(s):  
Mauro Dell’Amico ◽  
Giovanni Righini ◽  
Matteo Salani
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Branch And Price ◽  
Routing Problem ◽  
Price Approach

scholarly journals Analysing the Police Patrol Routing Problem: A Review

2020 ◽  
Vol 9 (3) ◽  
pp. 157 ◽  
Author(s):  
Maite Dewinter ◽  
Christophe Vandeviver ◽  
Tom Vander Beken ◽  
Frank Witlox
Keyword(s):  
Police Officers ◽  
Keyword Search ◽  
Hybrid Genetic Algorithm ◽  
Dynamic Vehicle Routing ◽  
Routing Problem ◽  
Police Patrol ◽  
Starting Point ◽  
Solution Methods ◽  
Routing Policies ◽  
Patrol Routing

Police patrol is a complex process. While on patrol, police officers must balance many intersecting responsibilities. Most notably, police must proactively patrol and prevent offenders from committing crimes but must also reactively respond to real-time incidents. Efficient patrol strategies are crucial to manage scarce police resources and minimize emergency response times. The objective of this review paper is to discuss solution methods that can be used to solve the so-called police patrol routing problem (PPRP). The starting point of the review is the existing literature on the dynamic vehicle routing problem (DVRP). A keyword search resulted in 30 articles that focus on the DVRP with a link to police. Although the articles refer to policing, there is no specific focus on the PPRP; hence, there is a knowledge gap. A diversity of approaches is put forward ranging from more convenient solution methods such as a (hybrid) Genetic Algorithm (GA), linear programming and routing policies, to more complex Markov Decision Processes and Online Stochastic Combinatorial Optimization. Given the objectives, characteristics, advantages and limitations, the (hybrid) GA, routing policies and local search seem the most valuable solution methods for solving the PPRP.

scholarly journals Branch-and-Price-and-Cut for the Periodic Vehicle Routing Problem with Flexible Schedule Structures

2019 ◽  
Vol 53 (3) ◽  
pp. 850-866 ◽  
Author(s):  
Ann-Kathrin Rothenbächer
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Branch And Price ◽  
Constraint Aggregation ◽  
Routing Problem ◽  
Shortest Path Problems ◽  
Acceleration Techniques ◽  
Periodic Vehicle Routing Problem ◽  
The Impact ◽  
Periodic Vehicle Routing

This paper addresses the periodic vehicle routing problem with time windows (PVRPTW). Therein, customers require one or several visits during a planning horizon of several periods. The possible visiting patterns (schedules) per customer are limited. In the classical PVRPTW, it is common to assume that each customer requires a specific visit frequency and offers all corresponding schedules with regular intervals between the visits. In this paper, we permit all kinds of schedule structures and the choice of the service frequency. We present an exact branch-and-price-and-cut algorithm for the classical PVRPTW and its variant with flexible schedules. The pricing problems are elementary shortest-path problems with resource constraints. They can be based on one of two new types of networks and solved with a labeling algorithm, which uses several known acceleration techniques, such as the [Formula: see text]-path relaxation and dynamic halfway points within bidirectional labeling. For instances in which schedule sets fulfill a certain symmetry condition, we present specialized improvements of the algorithm, such as constraint aggregation and symmetry breaking. Computational tests on benchmark instances for the PVRPTW show the effectiveness of our algorithm. Furthermore, we analyze the impact of different schedule structures on run times and objective function values. The online appendix is available at https://doi.org/10.1287/trsc.2018.0855 .

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