Efficient implementation of the genetic algorithm to solve rich vehicle routing problems

The aim of this paper is to further study the rich vehicle routing problem (RVRP), which is a well-known combinatorial optimization problem arising in many transportation and logistics settings. This problem is known to be subject to a number of real life constraints, such as the number and capacity...

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Published inOperational research Vol. 21; no. 3; pp. 1763 - 1791
Main Authors Rabbouch, Bochra, Saâdaoui, Foued, Mraihi, Rafaa
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2021
Springer Nature B.V
Subjects
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ISSN1109-2858
1866-1505
DOI10.1007/s12351-019-00521-0

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Abstract The aim of this paper is to further study the rich vehicle routing problem (RVRP), which is a well-known combinatorial optimization problem arising in many transportation and logistics settings. This problem is known to be subject to a number of real life constraints, such as the number and capacity limitation of vehicles, time constraints including ready and due dates for each customer, heterogeneous vehicle fleets and different warehouses for vehicles. A Genetic Algorithm (GA)-based approach is proposed to tackle this highly constrained problem. The proposed approach efficiently resolves the problem despite its high complexity. To the best of our knowledge, no GA have been used for solving multi-depot heterogeneous limited fleet VRP with time windows so far. The new algorithm has been tested on benchmark and real-world instances. In fact, promising computational results have shown its good cost-effectiveness.
AbstractList The aim of this paper is to further study the rich vehicle routing problem (RVRP), which is a well-known combinatorial optimization problem arising in many transportation and logistics settings. This problem is known to be subject to a number of real life constraints, such as the number and capacity limitation of vehicles, time constraints including ready and due dates for each customer, heterogeneous vehicle fleets and different warehouses for vehicles. A Genetic Algorithm (GA)-based approach is proposed to tackle this highly constrained problem. The proposed approach efficiently resolves the problem despite its high complexity. To the best of our knowledge, no GA have been used for solving multi-depot heterogeneous limited fleet VRP with time windows so far. The new algorithm has been tested on benchmark and real-world instances. In fact, promising computational results have shown its good cost-effectiveness.
Author Rabbouch, Bochra
Saâdaoui, Foued
Mraihi, Rafaa
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  organization: Ecole Supérieure de Commerce de Tunis, Université de Manouba
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Issue 3
Keywords Time windows
Heterogeneous limited fleet
Genetic algorithm
Multi depot
Rich VRP
MDHVRPTW
VRPLIB
Combinatorial optimization problem
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Snippet The aim of this paper is to further study the rich vehicle routing problem (RVRP), which is a well-known combinatorial optimization problem arising in many...
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SubjectTerms Business and Management
Combinatorial analysis
Computational Intelligence
Constraints
Genetic algorithms
Logistics
Management Science
Operations Research
Operations Research/Decision Theory
Optimization
Original Paper
Route planning
Vehicle routing
Vehicles
Windows (intervals)
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Title Efficient implementation of the genetic algorithm to solve rich vehicle routing problems
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