real coded genetic algorithm, rcga, is the type of ga which operates on chromosomes with real valued parameters. different mutation and crossover operations are defined for rcga. one usable crossover for this kind of ga is to consider its chromosomes simply as bit strings and utilize the same operations as binary coded ga. in this paper, we attempt to show that this kind of crossover can not ha...

Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...

determining the optimal location of wells with the aid of an automated search algorithm is a significant and difficult step in the reservoir development process. it is a computationally intensive task due to the large number of simulation runs required. therefore,the key issue to such automatic optimization is development of algorithms that can find acceptable solutions with a minimum number of...

Due to the complex structural issues and increasing number of design variables, a rather fast optimization algorithm to lead to a global swift convergence history without multiple attempts may be of major concern. Genetic Algorithm (GA) includes random numerical technique that is inspired by nature and is used to solve optimization problems. In this study, a novel GA method based on self-a...

In this paper, a novel algorithm for the load flow analysis problem in an islanded microgrid is proposed. The problem is modeled without any slack bus by considering the steady state frequency as one of the load flow variables. To model different control modes of DGs, such as droop, PV and PQ, in an islanded microgrid, a new formula for load flow equations is proposed. A hybrid optimization alg...

A new image denoising algorithm is proposed. GA-ELM algorithm uses genetic algorithm (GA) to decide weights in the Extreme learning Machine algorithm. It has better global optimal characteristics than traditional optimal algorithm. In this paper, we used GA-ELM to do image denoising researching work. Firstly, this paper uses training samples to train GA-ELM as the noise detector. Then, we utili...

among the several non-conventional processes, electrical discharge machining (edm) is the most widely and successfully applied for the machining of conductive parts. in this technique, the tool has no mechanical contact with the work piece and also the hardness of work piece has no effect on the machining pace. hence, this technique could be employed to machine hard materials such as super allo...

This paper deals with multi-period project portfolio selection problem. In this problem, the available budget is invested on the best portfolio of projects in each period such that the net profit is maximized. We also consider more realistic assumptions to cover wider range of applications than those reported in previous studies. A novel mathematical model is presented to solve the problem, con...

In Vitro Fertilization Genetic Algorithm (IVF/GA) is a recently created algorithm that combine the concepts of Genetic Algorithm and In Vitro Fertilization. The IVF/GA has the aim to improve the performance of Genetic Algorithm with the addition of IVF-Inspired mechanisms that better exploit the information of individuals. The Multimensional Knapsack Problem (MKP) is a complex combinatorial pro...

This paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. The objective is to minimize the weighted sum of makespan and maximum tardiness. Three meta-heuristic methods based on genetic algorithm (GA), imperialist competitive algorithm (ICA) and a hybrid approach of GA a...