TITLE:
Optimizing a Transportation System Using Metaheuristics Approaches (EGD/GA/ACO): A Forest Vehicle Routing Case Study
AUTHORS:
Hossein Havaeji, Thien-My Dao, Tony Wong
KEYWORDS:
Metaheuristics Algorithms, Transportation Costs, Optimization Approach, Cost Minimisation
JOURNAL NAME:
World Journal of Engineering and Technology,
Vol.12 No.1,
February
8,
2024
ABSTRACT: The
large-scale optimization problem requires some optimization techniques, and the
Metaheuristics approach is highly useful for solving difficult optimization
problems in practice. The purpose of the research is to optimize the transportation
system with the help of this approach. We selected forest vehicle routing data
as the case study to minimize the total cost and the distance of the forest
transportation system. Matlab software helps us find the best solution for this
case by applying three algorithms of Metaheuristics: Genetic Algorithm (GA),
Ant Colony Optimization (ACO), and Extended Great Deluge (EGD). The results
show that GA, compared to ACO and EGD, provides the best solution for the cost
and the length of our case study. EGD is the second preferred approach, and ACO
offers the last solution.