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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...
Very recently bacterial foraging has emerged as a powerful technique for solving optimization problems. In this paper, we introduce a micro-bacterial foraging optimization algorithm, which evolves with a very small population compared to its classical version. In this modified bacterial foraging algorithm, the best bacterium is kept unaltered, whereas the other population members are reinitialized...
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