Improving the Solution of Traveling Salesman Problem Using Genetic, Memetic Algorithm and Edge assembly Crossover

Gucht, The effects of population size, heuristic crossover and local improvement on a genetic algorithm for the traveling salesman problem, in: Proc. Johnson,

The multi-step crossover fusion (MSXF) was proposed by Yamada and Nakano as a unified operator of a local search method and a recombination operator in genetic local search..

In this paper, we propose new crossover operators by using the OR and XOR operations to improve multi-objective evolutionary algorithms applied to design optical

This paper studies the existing algorithms of minimum set cover problem and proposes a heuristic approach to solve the problem using modified hill climbing algorithm.. The

This paper presented two algorithms for solving the grid task scheduling problem through a combination of a genetic algorithm (GA), which is a global search

• To locate modifications and changes in the construction materials (original building materials were adobe, masonry), rebar structure whilst later modi fications included bricks

The objective of this research is to optimize the EC value of nutrient solution on each generative stage using Artificial Neural Network (ANN) and Genetic Algorithms (GA).. ANN

Another useful algorithm for multiple DNA sequence alignment using genetic algorithms and divide-and-conquer techniques [9] was proposed in which optimal cut