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Biogeography-Based Optimization (BBO) is a bio-inspired and population based optimization algorithm. This is mainly formulated to optimize functions of discrete variables. But the convergence of BBO to the optimum value is slow as it lacks in exploration ability. The proposed Accelerated Biogeography-Based Optimization (ABBO) technique is an improved version of BBO. In this paper, authors accelerated...
Biogeography-Based Optimization (BBO) is a recently developed global optimization algorithm and has shown its ability to solve complex optimization problem. The convergence of original BBO to the optimum value is slow as it lacks the exploration ability. An Accelerated Biogeography-Based Optimization (ABBO) technique is proposed in this paper to solve economic load dispatch problem. In this paper,...
Enhanced Biogeography-Based Optimization (EBBO) technique is an improved version of BBO. BBO mainly uses the idea of probabilistically sharing features (Migration operator) among solutions based on the fitness values. The exploitation ability of BBO is good in comparison to many optimization techniques due to efficient sharing of information among solutions. However, migration operator creates similar...
This paper proposes fusion of synchronous germ computing (SGC) with twin swarm intelligence (TSI) technique named as SGCTSI to enhance quality of global solutions with faster convergence of multimodal functions. In this paper, initially the authors tried to increase the speed of bacteria by updating bacteria positions synchronously, which is treated as SGC. In SGC, all the bacteria update their positions...
This paper presents fusion of Bacterial Foraging with parameter free Particle Swarm Optimization (HBF-pfPSO). The proposed technique is used to enhance quality of global optima of multimodal functions. The authors propose two major modifications in Bacterial Foraging Optimization (BFO). Firstly, all bacteria position and direction are updated after all fitness evaluations instead of each fitness evaluation...
Biogeography-Based Optimization (BBO) is a new bio-inspired and population based optimization algorithm. The convergence of original BBO to the optimum value is slow. Intelligent Biogeography-Based Optimization (IBBO) technique is a hybrid version of BBO with Bacterial Foraging algorithm (BFA). In this paper, authors integrate the bacterial intelligence feature of BFA to decide the valid emigration...
This paper contributes a novel Particle Swarm Optimization (PSO) method. The particle is updated not only by the best position in history (pbest) and the best position among all the particles in the swarm (gbest), but also using the position that is nearest neighbor of pbest. Additionally, we introduce a modified PSO algorithm based on the fuzzy clustering of particles to communication with the nearest...
In this paper, the authors propose a new evolutionary optimization technique i.e. modified biogeography-based optimization (MBBO). This technique is an improved version of BBO with each solution is directly encoded by floating point. BBO is a new bio-inspired and population based optimization algorithm for global optimization. The exploitation ability of BBO method is good but it lacks in exploration...
In this paper, the authors propose a new evolutionary optimization i.e. synchronous bacterial foraging optimization (SBFO). The SBFO can be used for optimization of multimodal and high dimensional functions. It also enhances computational throughput and global search capability. The convergence of original BFO to the optimum value is very slow and its performance is also heavily affected with increased...
Soft computing applications to antenna design are becoming the potential solution provider as reflected from the number of papers published in various journals. Resonant frequency of rectangular microstrip antenna having various substrate thicknesses are generally calculated using the standard expressions presented in literatures. In this paper, hybridizing bacterial foraging optimization technique...
Particle swarm optimization is an evolutionary optimization technique conceived in recent time has many advantages over genetic algorithm. But it is yet to be applied in the parameters calculations of microstrip patch antenna. In this paper, a novel technique is developed to apply particle swarm optimization technique in conjunction with the developed standard equation to accurately calculate the...
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