In our recent research, we showed results of the comparative study on effects of using several kinds of scheduling evaluation criteria as the fitness function of a genetic algorithm for job-shop scheduling. From these results, we obtained that the idle time criterion sometimes can provide a good makespan-minimizing schedule for a job-shop scheduling problem. In this paper, according to the abov...

In this paper a hybrid algorithm based on exploration power of the Genetic algorithms and exploitation capability of Nelder Mead simplex is presented for global optimization of multi-variable functions. Some modifications are imposed on genetic algorithm to improve its capability and efficiency while being hybridized with Simplex method. Benchmark test examples of structural optimization with a...

t his paper presents a new feature selection approach for automatically extracting   ms lesions in 3d mr images. presented method is applicable to different types of ms lesions. in this method, t1, t2 and flair images are firstly preprocessed. in the next phase, effective features to extract ms lesions are selected by using a genetic algorithm. the fitness function of the genetic algorithm is t...

many studies are performed by researchers about shell and tube heat exchanger but the multi-objective big bang-big crunch algorithm (mobba) technique has never been used in such studies. this paper presents application of thermal-economic multi-objective optimization of shell and tube heat exchanger using mobba. for optimal design of a shell and tube heat exchanger, it was first thermally model...

This paper presents automatic test case generation technique. Multi population genetic algorithm is used to generate test cases. Fitness function is based on the multiple condition decision coverage criteria. MATLAB Gatool is used for implementing the test case generation algorithm. It generates efficient and effective test cases. Test cases are optimized using multi population genetic algorith...

This paper presents a genetic-algorithm driven, cognitive radio decision engine that determines the optimal radio transmission parameters for single and multicarrier systems. Determining the appropriate radio parameters given a dynamic wireless channel environment is the primary feature of cognitive radios for wireless communication systems. Genetic algorithms (GA) are designed to select the op...

The cooperative game of global temperature lacks automaticity and emotional jamming. To solve this issue, an agent-based modelling method is developed based on Milinski’s noncooperative game experiments. In addition, genetic algorithm is used to improve the investment strategy of each agent. Simulations are carried out by designing different coding schemes, mutation schemes, and fitness functio...

Because of the complicated conditions, great deformation, high stress, multi-variables, high non-linearity, the algorithm for structure optimization and its application in tunnel engineering has just been at the right beginning. However, how to make optimized design of structure for tunnel section, reduce excavation and increase support is a very urgent task now. Artificial intelligence shows e...

In the field of robotics, before the conception of any approach to solve robot path planning, it would be the procedure to derive a model for the problem and solution theoretically, then going for simulations to verify the derived model and then implemented and validated in the real time applications, by taking into account many real time factors. This survey studies the evolution of implementa...

The tailoring of an evolutionary algorithm to a specific problem is typically a time-consuming and complex process. Over the years, several approaches have been proposed for the automatic adaptation of parameters and components of evolutionary algorithms. We focus on the evolution of mating selection fitness functions and use as case study the Circle Packing in Squares problem. Each individual ...