A Two-Phase Method to Periodic Vehicle Routing Problem with Variable Service Frequency

2018 ◽  
pp. 525-538
Author(s):  
Eduyn López-Santana ◽  
Carlos Franco ◽  
Germán Méndez Giraldo
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Phase Method ◽  
Two Phase ◽  
Routing Problem ◽  
Periodic Vehicle Routing Problem ◽  
Service Frequency ◽  
Periodic Vehicle Routing

Multi-depot periodic vehicle routing problem with due dates and time windows

2017 ◽  
Vol 69 (2) ◽  
pp. 296-306 ◽  
Author(s):  
Roberto Cantu-Funes ◽  
M. Angélica Salazar-Aguilar ◽  
Vincent Boyer
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Due Dates ◽  
Routing Problem ◽  
Periodic Vehicle Routing Problem ◽  
Periodic Vehicle Routing

scholarly journals A Cluster-First Route-Second Heuristic Approach to Solve The Multi-Trip Periodic Vehicle Routing Problem

2019 ◽  
Vol 20 (2) ◽  
pp. 68
Author(s):  
Annisa Kesy Garside ◽  
Nabila Rohmatul Laili
Keyword(s):  
Integer Programming ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Phase 1 ◽  
Working Hours ◽  
Real Problem ◽  
Phase 2 ◽  
Routing Problem ◽  
Periodic Vehicle Routing Problem ◽  
Periodic Vehicle Routing

This paper discusses periodic vehicle routing problems that allow vehicles to travel on multiple trips in a single day. It is known as the Multi-Trip Periodic Vehicles (MTPVRP) Problem Route. Cluster-first route-second (CFRS) heuristics to solve MTPVRP was proposed in this study. In phase 1, customers were divided into clusters using the formulation of integer programming. Phase 2 determined the route of the cluster and verifies that the total journey time to visit the trips does not exceed the working hours of the vehicle. The implementation of the heuristic CFRS to solve the real problem faced by the LPG distributor shows that the procedure could provide a better routing solution.

Robust Periodic Vehicle Routing Problem with Time Windows under Uncertainty: An Efficient Algorithm

2018 ◽  
Vol 22 (11) ◽  
pp. 4626-4634 ◽  
Author(s):  
A. Salamatbakhsh-Varjovi ◽  
R. Tavakkoli-Moghaddam ◽  
M. Alinaghian ◽  
E. Najafi
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Efficient Algorithm ◽  
Time Windows ◽  
Routing Problem ◽  
Periodic Vehicle Routing Problem ◽  
Periodic Vehicle Routing

scholarly journals A unified model framework for the multi-attribute consistent periodic vehicle routing problem

PLoS ONE ◽  
2020 ◽  
Vol 15 (8) ◽  
pp. e0237014
Author(s):  
Maria Gulnara Baldoquin ◽  
Jairo A. Martinez ◽  
Jenny Díaz-Ramírez
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Unified Model ◽  
Model Framework ◽  
Routing Problem ◽  
Periodic Vehicle Routing Problem ◽  
Periodic Vehicle Routing

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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