In nature-inspired metaheuristic algorithms, two key components are local intensification and global diversification, and their interaction can significantly affect the efficiency of a metaheuristic algorithm. However, there is no rule for how to balance these important components. In this paper, we provide a first attempt to give some theoretical basis for the optimal balance of exploitation a...

this paper proposes a novel hybrid algorithm namely apso-bfo which combines merits of bacterial foraging optimization (bfo) algorithm and adaptive particle swarm optimization (apso) algorithm to determine the optimal pid parameters for control of nonlinear systems. to balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

Here, metaheuristic search techniques are applied for robotic path planning. Robot has to move from its starting point called source point to final point called as destination point with minimum number of moves and iteration. Here both cuckoo search and bat algorithms are applied for the proposed problem and simulation results are compared. The techniques are applied for different number of pop...

In this paper, we propose a novel discrete cuckoo search algorithm (DCS) for solving spherical Traveling Salesman Problem (TSP) where all points are on the surface of a sphere. The algorithm is based on the Lévy flight behaviour and brood parasitic behaviour. The proposed algorithm applies study operator, the ”A” operator, and 3-opt operator to solutions in the bulletin board to speed up the co...

DNA microarrays have been applied successfully in diverse research fields such as gene discovery, disease diagnosis and drug discovery. The roles of the genes and the mechanisms of the underlying diseases can be identified using microarrays. Biclustering is a two dimensional clustering problem, where we group the genes and samples simultaneously. It has a great potential in detecting marker gen...

In this paper, a new meta-heuristic path planning algorithm, the cuckoo–beetle swarm search (CBSS) is introduced to solve problems of heterogeneous mobile robots. Traditional algorithms, e.g., genetic algorithms (GA), particle (PSO), beetle optimization (BSO), and cuckoo (CS), have such as tenancy become trapped in local minima because premature convergence weakness global capability planning. ...

<span lang="EN-US">A novel metaheuristic optimization algorithm based on cuckoo search (CSA) is presented to solve the construction site layout planning problem (CSLP). CSLP a complex with various applications, such as plant layout, and computer chip layout. Many researchers have investigated by applying many algorithms in an exact or heuristic approach. Although both methods yield promis...