|
|
|
|
|
Esra?a Alkafaween, Ahmad Hassanat, Ehab Essa and Samir Elmougy
The genetic algorithm (GA) is a well-known metaheuristic approach for dealing with complex problems with a wide search space. In genetic algorithms (GAs), the quality of individuals in the initial population is important in determining the final optimal ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Fakhar Uddin, Naveed Riaz, Abdul Manan, Imran Mahmood, Oh-Young Song, Arif Jamal Malik and Aaqif Afzaal Abbasi
The travelling salesman problem (TSP) is perhaps the most researched problem in the field of Computer Science and Operations. It is a known NP-hard problem and has significant practical applications in a variety of areas, such as logistics, planning, and...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shaolong Yang, Jin Huang, Weichao Li and Xianbo Xiang
A growing number of researchers are interested in deploying unmanned surface vehicles (USVs) in support of ocean environmental monitoring. To accomplish these missions efficiently, multiple-waypoint path planning strategies for survey USVs are still a ke...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andrei Gorchakov
Pág. 1 - 5
When developing parallel methods for solving many numerical methods for solving applied problems, in particular the branch-and-bound method, the problem of load balancing arises. The choice of implementation options at the moment has been proposed quite ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sara Pérez-Carabaza, Akemi Gálvez and Andrés Iglesias
Ant Colony Optimization (ACO) encompasses a family of metaheuristics inspired by the foraging behaviour of ants. Since the introduction of the first ACO algorithm, called Ant System (AS), several ACO variants have been proposed in the literature. Owing t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chandra Agung, Natalia Christine
Pág. 69 - 75
The subject of this research is distance and time of several city tour problems which known as traveling salesman problem (tsp). The goal is to find out the gaps of distance and time between two types of optimization methods in traveling salesman problem...
ver más
|
|
|
|
|
|
|
|
|
|
|
Umberto Junior Mele, Luca Maria Gambardella and Roberto Montemanni
Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhibit issues when they try to scale up to real case scenarios with several hundred vertices. The use of Candidate Lists (CLs) has been brought up to cope with t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Giuseppe Lancia and Marcello Dalpasso
Given a Traveling Salesman Problem solution, the best 3-OPT move requires us to remove three edges and replace them with three new ones so as to shorten the tour as much as possible. No worst-case algorithm better than the T(??3)
T
(
n
3
)
enumeration o...
ver más
|
|
|
|
|
|
|
|
|
|
|
Christos Papalitsas, Panayiotis Karakostas and Theodore Andronikos
The purpose of this paper is to assess how three shaking procedures affect the performance of a metaheuristic GVNS algorithm. The first shaking procedure is generally known in the literature as intensified shaking method. The second is a quantum-inspired...
ver más
|
|
|
|
|
|
|
|
|
|
|
Erna Budhiarti Nababan, Opim Salim Sitompul, Yuni Cancer
Pág. 87 - 100
Population size of classical genetic algorithm is determined constantly. Its size remains constant over the run. For more complex problems, larger population sizes need to be avoided from early convergence to produce local optimum. Objective of this rese...
ver más
|
|
|
|
|
|