[PDF] Top 20 Genetic algorithms for the traveling salesman problem

... Gucht, The effects of population size, heuristic crossover and local improvement on a genetic algorithm for the traveling salesman problem, in: Proc. Johnson, Local[r] ... See full document

... example. Genetic algorithms can be used to solve the traveling salesman problem ...this problem, it can be stated in two ways. Informally, there is a traveling ... See full document

... NP-hard problem. So GA can be applied to find the city sequence with optimal travelling cost, that is the solution of ...to the stochastic nature of GA, it does not ensure an optimal solution ... See full document

... Abstract— The Traveling salesman problem (TSP) is to find a tour of a given number of cities (visiting each city exactly once) where the length of this tour is ...additions. ... See full document

... distances, the mission is to find the shortest possible tour that visits each city exactly once still keeping the new cost ...reanalyze the rules giving the optimal solution to ... See full document

... scheduling problem is a hard Combinatorial Optimization problem widely studied over the ...consideration the range of variables related to the planning process of vehicles and drivers, ... See full document

... solve the resource-constrained multiple project scheduling problem ...(RC-MPSP). The proposed approach worked based on using genetic operators with fuzzy logic controller (FLC) through ... See full document

... for the Bus Driver Rostering Problem and proposes the hybridization of column generation and genetic algorithms to achieve good quality rosters in short ...time. The ... See full document

... – the RPGA algorithm – based on Genetic Algorithms to solve the Undirected Rural Postman Problem ...(RPP). The RPP is a particular Arc Routing Problem, with many ... See full document

... of the Generalized Traveling Salesman Problem in programming pro- cesses of machines in industries, postal routing and layout of ...on the total cost of an optimal so- lution. Many ... See full document

... heuristic algorithms based on the classic Condorcet ranking ...to the ranking of an algorithm among a set being object of ...on the set of natural numbers to create a ranking. The ... See full document

... ABSTRACT. The Traveling Salesman Problem (TSP) is one of the most well-known and studied problems of Operations Research field, more specifically, in the Combinatorial ... See full document

... of the main approaches to parallel genetic algorithms ...(PGA). Problem–solving GA based environments aim at providing support for the application of GA to specific ...by the ... See full document

... two algorithms for solving the grid task scheduling problem through a combination of a genetic algorithm (GA), which is a global search algorithm, and the firefly algorithm (FA), which ... See full document

... With the increasing amount of molecular biological structures available, docking approaches have been very important and useful tools in structure-based rational drug discovery and design (Gane and Dean, ... See full document

... compare the performance of different learning ...neither the pure Lamarckian nor pure Baldwinian strategy was found to be consistently ...that the 20% and 40% partial Lamarckian search strategies ... See full document

... examining the time series of fitness values, an increase in fitness was ...out the best individual every 10 time steps and plug the virtual user's values into the stand-alone ...as the ... See full document

... of the rich sources of inspiration for inventing new intelligent ...of the scientific fields that are based on natural swarms, such as ant colonies, bee colonies, group behavior of bacterium, rivers (group ... See full document

... observe the performance of HCGA were executed in a PC-Asus with a clock of 1,8 GHz and 256 Mbytes of RAM and the source program is in ANSI ...presents the mean deviation and CPU time of ... See full document

... of the work on self-adaptive genetic optimiza- tion strategy. The strategy introduces meta algorithm, at the level of the individual genetic algorithms with a set of ... See full document