Software testing is a critical and labor-intensive activity in software engineering. Much research has been done to help automate test case generation. This research proposes a new approach to structural test case generation. It uses a specialized genetic algorithm called Dynamic-radius Species-conserving Genetic Algorithm (DSGA) to find a structurally complete set of test cases for the Triangl...

To reproduce an image, it is necessary to map out of gamut colors of the image to destination gamut. It is clear that the best color gamut mapping introduces the perceptually closest image to the original one. In this study, a new color gamut mapping is purposed by the aid of Genetic Algorithm (GA). The color difference between the original and mapped images based on S-LAB formula was chosen as...

Water reservoir programming studies aim to determine the final cultivated land area based on predefined agricultural models and water requirements. Dam utilization rule curve is also provided in such studies. The system of Dez dam water resources was simulated applying the basic information in order to determine the capability of its reservoir to provide the objectives of the performed plan. As...

A new hybrid algorithm of Particle Swarm Optimization and Genetic Algorithm (PSOGA) is presented to get the optimum design of truss structures with discrete design variables. The objective function chosen in this paper is the total weight of the truss structure, which depends on upper and lower bounds in the form of stress and displacement limits. The Particle Swarm Optimization basically model...

Automatic path oriented test data generation is not only a crucial problem but also a hot issue in the research area of software testing today. In this paper genetic algorithm (GA) has been used as a robust metaheuristic search method under basis path testing coverage criteria. Two types of fitness function have been used, one is branch distance based fitness function (BDBFF) and other is appro...

Fitness distance correlation has been proposed as an analysis tool for the fitness function landscape of genetic algorithms. It has been shown that it works in some cases, but there are also counterexamples. We studied the fitness distance correlation and the optimal population size by two fitness functions with a translational minimum and with a meta-genetic algorithm. We discovered that the f...

ABSTRACT Introduction: The genetic algorithm is one of the essential theoretical mathematical models for simulating biological development. It widely used in many fields such as engineering, medicine, and economics. Objective: Use a model basis optimization high school students’ aptitude program. Methods: selection method by competition adopted to elect random crossover male probability with si...

In this paper, a simplified model with a lower order is first developed for a nuclear steam generator system and verified against some realistic environments. Based on this simplified model, a hybrid multi-input and multi-out (MrMO) control system, consisting of feedforward control (FFC) and feedback control (FBC), is designed for wide range conditions by using the genetic algorithm (GA) techni...