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Invasive weed optimization (IWO) has been found to be a simple but powerful algorithm for function optimization over continuous spaces. It has reportedly outperformed many types of evolutionary algorithms and other search heuristics when tested over both benchmark and real-world problems. This article describes the design of fractional-order proportional-integral-derivative (FOPID) controllers, using...
Fault detection and diagnosis can effect system reliability and avoid expensive maintenance. In a manufacturing process, a simple fault can lead to environmental damage. In this way, one of the most commonly applied fault detection method is the parameter estimation technique. In this paper, we present an advanced algorithm for the estimation of electrical machine parameters by combining two approaches:...
All areas relating to telecommunications, electricity distribution, and gas pipeline require Topological optimization. It also has a major importance in the computer communication industry, when considering network reliability. In this paper, we have used GA with specialized encoding, initialization, local search operators with specially designed crossover operator called alternating crossover [21]...
Robotic manipulators with three-revolute (3R) positional configurations are very common in the industrial robots (IRs). The capability of a robot largely depends on the workspace (WS) of the manipulator apart from other parameters. With the constraints in mind the optimization of the workspace is of prime importance in designing the manipulator. The present work aims at obtaining an optimal design...
The present study proposes an alternate method based on genetic algorithm (GA) to estimate the subsurface lithologic parameters such as P-wave velocity, the S-wave velocity and the density for subsurface earth layers occurring at a particular location. These are useful parameters to discriminate lithology and help in detecting hydrocarbons from seismic data. However, estimation of the lithologic parameters...
BitTorrent has emerged as an effective peer-to-peer application for digital content distribution in the Internet. However, selecting peers in BitTorrent for efficient content distribution still poses a number of challenges due to high heterogeneities of peers with varied rates of uploading bandwidth and dynamic content. This paper presents GA-BT, a genetic algorithm based peer selection optimization...
In this paper we propose an approach for test data generation using genetic algorithm. Our objective is to design a multi-population genetic algorithm using uniform crossover. In this paper we analyze the performance of proposed uniform crossover multi population genetic algorithm method with different combinations of factors that influence the test data generation strategy. For implementing multi-population...
Design of an optimal controller requires optimization of multiple performance measures that are often noncommensurable and competing with each other. Design of such a controller is indeed a multi-objective optimization problem. Being a population based approach; genetic algorithm (GA) is well suited to solve multi-objective optimization problems. This paper investigates the application of GA-based...
This paper studies the use of Genetic Algorithms (GA) in the design of Fuzzy Logic Controllers (FLC) and show how population size, probability of crossover and rate of mutation can effect the performance of the GA. The comparison of various parameters shows that GA is helpful in improving the performance of FLC. A fuzzy logic is fully defined by its membership function. What is the best to determine...
Driven by open global competition, rapidly changing technology, and shorter product life cycles, manufacturing organizations come across significant amount of uncertainty and hence continuous change. Customers' demand for a greater variety, high quality and competitive cost is in increasing trend. Flexible Manufacturing Systems (FMS) have brought in significant advantages and benefits to manufacturing...
In the present study, input-output relationships of metal inert gas welding process have modeled using radial basis function neural networks. As the performance of a neural network depends on its structure and parameters, some approaches have been developed to optimize them simultaneously. The performances of the developed approaches have been compared among them on some test cases. It has been observed...
This paper proposes an approach for the design of multiple power system stabilizers (PSS) for multi-area automatic generation control (AGC) system with new deregulated scenario. Here, the concept of DISCO participation matrix (DPM) is also included. The analysis is conducted considering three pre-defined cases, out of which one is the violation of contract case. The optimal parameters of the PSS are...
In many image-processing applications it is necessary to register multiple images of the same scene acquired by different sensors, or images taken by the same sensor but at different times. Mathematical modeling techniques are used to correct the geometric errors like translation, scaling and rotation of the input image to that of the reference image, so that these images can be used in various applications...
Predicting the structure of a protein from primary sequence is one of the challenging problems in Molecular biology. In this context, protein structural class information provides a key idea of their structure and also other features related to the biological function. In this paper we present a new optimization approach based on Genetic algorithm (GA) and artificial immune system (AIS) for predicting...
Medical image fusion has been used to derive the useful information from multi modal medical images. The proposed methodology introduces evolutionary approaches for robust and automatic extraction of information from different modality images. This evolutionary fusion strategy implements multiresolution decomposition of the input images using wavelet transform. It is because, the analysis of input...
Electro Chemical Machining (ECM) is one of the most widely used advanced machining processes to produce complicated shapes from electrically conductive but difficult to machine materials. This paper presents a Fuzzy Logic (FL) - based modeling of ECM process and optimization of its rule base, data base and consequent part utilizing a Genetic Algorithm (GA). A binary coded GA has been used for the...
Ant Colony Optimization (ACO) is more suitable for combinatorial optimization problems. This paper proposes Genetic Evolving Ant Colony Optimization (EACO) method for solving unit commitment (UC) problem. The EACO employs Genetic Algorithm (GA) for finding optimal set of ACO parameters, while ACO solves the UC problem. Problem formulation takes into consideration the minimum up and down time constraints,...
Bio-inspired evolutionary algorithms are probabilistic search methods that simulate the natural biological evolution or the behaviour of biological entities. Such algorithms can be used to obtain near optimal solutions in optimization problems, for which traditional mathematical techniques may fail. This paper does a comparative study of results of five evolutionary algorithms: Genetic Algorithm (GA),...
In this paper we have used a real coded genetic algorithm for finding the global minimum energy conformation of two small molecules viz. Pseudoethane and 1,2,3-trichloro-l-fluoro-propane based on a potential function. Finding the global minimum of this function is very difficult because it has a large number of local minima, which grows exponentially with molecule size. Computational results are obtained...
In our previous work, we have presented a method for genetically synthesizing software architecture design. Synthesis begins with a responsibility dependency graph and domain model for a system, and results in a full architecture proposal through the application of design patterns and architectural styles. In this paper, we study the method of reproduction in the genetic algorithm. More specifically,...
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