A genetic algorithm for efficient delivery vehicle operation planning considering traffic conditions

Authors:
Yoong-Seok Yoo;Jae-Yearn Kim
Affiliations:
Department of Industrial Engineering, Hanyang University, Sungdong-gu, Seoul, Korea;Department of Industrial Engineering, Hanyang University, Sungdong-gu, Seoul, Korea
Venue:
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part II
Year:
2010

Citing 6
Cited 0

A tabu search heuristic for the vehicle routing problem

Management Science
Parallel genetic algorithms for the earliness-tardiness job scheduling problem with general penalty weights

Computers and Industrial Engineering
Genetic algorithms + data structures = evolution programs (3rd ed.)

Genetic algorithms + data structures = evolution programs (3rd ed.)
The vehicle routing problem

The vehicle routing problem
Genetic Algorithms and Manufacturing Systems Design

Genetic Algorithms and Manufacturing Systems Design
A genetic algorithm for the vehicle routing problem

Computers and Operations Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

To ensure customer satisfaction, companies must deliver their product safely and within a fixed time. However, it is difficult to determine an inexpensive delivery route when given a number of options. Therefore, an efficient vehicle delivery plan is necessary. Until now, studies of vehicle routes have generally focused on determining the shortest distance. However, vehicle capacity and traffic conditions are also important constraints. We propose using a modified genetic algorithm by considering traffic conditions as the most important constraint to establish an efficient delivery policy for companies. Our algorithm was tested for fourteen problems, and it showed efficient results.