They can be used to find approximate solutions to numerical optimization problems in cases where finding the exact optimum is prohibitively expensive, or where no algorithm is known. However, such applications can encounter problems that sometimes delay, if not prevent, finding the optimal solutions ...
In addition, we propose a diversity operator to be used instead of mutation and also maintain an archive of good solutions. Although the purpose of the proposed algorithm is to cover a wider range of problems, it may not be the best algorithm for all types of problems. To judge the ...
A multi-objective genetic algorithm is used for optimization of the fuzzy logic controller. Both the 75th floor acceleration response of the structure and the stroke of the STMD have been used as the objective functions for this multi-objective optimization problem. Because a multi-objective ...
This study considers the application of a genetic algorithm (GA) to the basic vehicle routing problem (VRP), in which customers of known demand are supplied from a single depot. Vehicles are subject to a weight limit and, in some cases, to a limit on the distance travelled. Only one vehi...
GADMA implements methods for automatic inference of the joint demographic history of multiple populations from the genetic data. GADMA is a command-line tool. Basic pipeline presents a series of launches of the global search algorithm followed by the local search optimization. GADMA provides two ty...
Recently proved successful for variants of the vehicle routing problem (VRP) involving time windows, genetic algorithms have not yet shown to compete or challenge current best search techniques in solving the classical capacitated VRP. A new hybrid genetic algorithm to address the capacitated VRP is ...
You can stop the algorithm at any time by clicking the Stop button on the plot window. For example, to display the best function value, set options as follows: options = optimoptions('ga','PlotFcn','gaplotbestf'); To display multiple plots, use a cell array of built-in plot ...
A -point crossover is used to maintain diversity in the solution space. The wavelength assignment to lightpaths in fittest individuals is performed using a special graph-coloring technique. We compare the single objective results with those obtained by known heuristics like the First-Fit algorithm....
Genetic algorithm is a heuristic population-based search method that incorporates three primary operators: crossover, mutation and selection. Selection operator plays a crucial role in finding optimal solution for constrained optimization problems. In this paper, an improved genetic algorithm (IGA) based...
To overcome the first weakness, we can use fuzzy centroid, and for second weakness is to implement the genetic algorithm to search the global optimum solution. Our research combines the genetic algorithm and Fuzzy K-Prototype to accommodate these two weaknesses. We set up two multivariate data ...