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In this paper, we have demonstrated the electrical characteristics of Si Gate-All-Around (GAA) Nanowire (NW) field-effect transistor (FET) using numerical simulation. GAA devices are considered to be the ultimate architecture among all multi-gate devices. During fabrication, the cross-section of a GAA device may be elliptical instead of perfectly circular. The effective diameter of such elliptical...
Artificial bee colony is a recently proposed metaheuristic optimization technique and is a new member of swarm intelligence based algorithms. It mimics the foraging behavior of honey bees. The performance of Artificial Bee Colony (ABC), like other metaheuristics, is heavily dependent on the tradeoff between their exploration and exploitation aptitude. In this paper a variant called Local Global variant...
Foraging behavior has inspired different algorithms to solve real-parameter optimization problems. One of the most popular algorithms within this class is the Artificial Bee Colony (ABC). In the present study the food source is initialized by comparing the food source with worst fitness and the evaluated mean of randomly generated food sources (population). Further the scout bee operator is modified...
ABC is an optimization technique, used in finding the best solution from all feasible solutions. However, there is still an insufficiency in ABC regarding improvement in exploitation and convergence speed. In order to improve the performance of ABC we used mean mutation operator (MMO), which uses a linear combination of Gaussian and Cauchy distributions. This convoluted distribution produces larger...
The Artificial Bee Colony (ABC) algorithm, proposed by Karaboga in 2005 for real-parameter optimization, is a recently introduced optimization algorithm which simulates the foraging behaviour of a bee colony. The proposed variant employs colony size (population size) reduction mechanism during the evolutionary process. Then modification is done to enhance the perturbation scheme. Further, in order...
A poor balance between exploration and exploitation may result in a weak optimization method which may suffer from premature convergence, trapping in a local optima, and stagnation. In order to enhance the global convergence and to prevent to stick on a local solution of the ABC, an improvement based on golden section search method is proposed in this paper. The local search algorithm assists in the...
Artificial Bee Colony (ABC) algorithm is one approach that has been used to find an optimal solution in numerical optimization problems. This algorithm is inspired by the foraging behavior of honey bees when seeking a quality food source. ABC can sometimes trap into local optimum and also slow to converge. In ABC, the employed bees and onlooker bees carry out exploration and exploitation use the same...
Differential Evolution (DE) is a simple, efficient algorithm which has reportedly outperformed many other optimization algorithms in terms of convergence speed and robustness over common benchmark problems and real world applications. However, one is required to set the values of the control parameters of DE for each problem. Such parameter tuning is a time consuming task. The proposed scheme dynamically...
ABC (Artificial Bee Colony) is one of the most recent nature inspired algorithm (NIA) based on swarming metaphor. Proposed by Karaboga in 2005, ABC has proven to be a robust and efficient algorithm for solving global optimization problems over continuous space. In this paper, we propose a modified version of the ABC to improve its performance, in terms of converging to individual optimal point and...
Artificial Bee Colony (ABC) algorithm is an optimization algorithm based on the intelligent behaviour of honey bee swarm. ABC can be initialized with either a uniform or a non-uniform distribution. The decision regarding which to use depends on how much is known about the location of the optimum. Generally uniform distributions are preferred since they best reflect the lack of knowledge about the...
Artificial Bee Colony or ABC is one of the newest additions to the class of population based Nature Inspired Algorithms (NIA). In the present study we suggest some modifications in the structure of basic ABC to further improve its performance. The corresponding algorithm proposed in the present study is named Intermediate ABC (I-ABC). In I-ABC, the potential food sources are generated by using the...
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