International Journal of Advanced Research In Computer Science and Software EngineeringS. Khattar, and Dr.P. Gosawmi, "An Efficient Solution of Travelling Salesman Problem Using Genetic Algorithm", International Journal of Advanced Research in Computer Science and Software Engineering, vol. 4, no. 5...
generally composed of coded genotype strings, statistically definedcontrol parameters, a fitness function, genetic operations (reproduction, crossover and mutation), and mechanisms for selection and encoding of the solutions as genotype strings. The basic flowchart of agenetic algorithmis shown inFigure ...
The random values \({p}_{j}^{* }\) are, in turn, selected from a uniform distribution, whose lower and upper limits are given by the gene boundaries (see the subsection “Genetic algorithm parameters” in the Methods Section for more details). These two operations allow the parameter ...
The conceptual model is developed and modeled, and solutions are explored using General Algebraic Modeling System software (GAMS), as well as Multiple Objective Particle Swarm Optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGAII) algorithms in small dimensions (Freitas et al.,...
E.Use of genetic algorithms to solve production and operations management problems: A review. International Journal of Production Research . 2003Aytug, H., M. Khouja, and F.E. Vergara. (2003). "Use of Genetic Algorithm to Solve Production and Operations Management Problems: A Review." Inte...
The term ‘genetic algorithm’, which nowadays is universally identified as the abbreviated GA, was first used by John Holland [34]. His book, Adaptation in Natural and Artificial Systems, was instrumental in creating what is now a flourishing field of research and application that goes much ...
genetic algorithm (GA) to cooperative control in MAS. First, existing studies in this area often focus on simple agent dynamics, such as single or double integrators. The cooperative control of high-order nonlinear MAS needs to be investigated, leaving a gap in understanding how GA can be ...
[46]. The author gives a clear definition of the fitness function used in the research. The authors did not provide the problem encoding or description of the chromosome or individual. As a result, it is unclear about the implementation of the algorithm in the service broker policy. Another ...
Genetic algorithm (GA) is a kind of method to simulate the natural evolvement process to search the optimal solution, and the algorithm can be evolved by four operations including coding, selecting, crossing and variation. The particle swarm optimization (PSO) is a kind of optimization tool base...
. We repeated the same steps until there are no more stops to discriminate or to connect to. With this algorithm, we made sure that there are no cycles, but there will be instances wherein not all stops will be part of the network. In such cases, they will be removed. In this ...