This paper summarizes the implementation and performance of Nondominated Sorting Genetic algorithm (NSGA-II) [2] for feature selection of remotely sensed hyperspectral imagery. Two step processes have been followed. In first step, a feature subset is selected with optimum spectral and texture information content resulting in a smaller space to be searched in the next step. In the second step, a...

The increasing complexity of the modern control systems has emphasized the idea of applying new approaches in order to solve design problems for different control engineering problems. This paper reports a performance comparison between traditional (linear PID controller) and evolvable methods (evolvable hardware controllers) applied to the problem of three-degrees-of-freedom manipulator contro...

A design and optimization of 3-5 GHz single ended Radio Frequency (RF) Low Noise Amplifier (LNA) for ultra-wide-band (UWB) applications using standard UMC 0.18 μm CMOS technology is reported. Designing of RF circuit components is a challenging job, since even after performing lengthy calculations and finding parameter values it is less guarantee that the design performs as expected. In view of ...

Non-dominated Sorting Genetic Algorithm (NSGA) has established itself as a benchmark algorithm for Multi objective Optimization. The determination of pareto-optimal solutions is the key to its success. However the basic algorithm for big problem gives less efficient results, which renders it less useful for practical applications. Among the variants of NSGA, several attempts have been made to r...

Multi-objective optimization methods are essential to resolve real-world problems as most involve several types of objects. Several multi-objective genetic algorithms have been proposed. Among them, SPEA2 and NSGA-II are the most successful. In the present study, two new mechanisms were added to SPEA2 to improve its searching ability a more effective crossover mechanism and an archive mechanism...

This study presents a multi-objective optimization approach for designing hybrid renewable energy systems electric vehicle (EV) charging stations that considers both economic and reliability factors as well seasonal variations in production consumption. Four algorithms, MOPSO, NSGA-II, NSGA-III, MOEA/D, were evaluated terms of their convergence, diversity, efficiency, robustness. Unlike previou...

This paper proposes a modified non-dominated sorting genetic algorithm (NSGA-II) for a bi-objective location-allocation model. The purpose is to define the best places and capacity of the distribution centers as well as to allocate consumers, in such a way that uncertain consumers demands are satisfied. The objectives of the mixed-integer non-linear programming (MINLP) model are to (1) minimize...