An Optimization Algorithm Based on Bacteria Behavior

Support Vector Machine Optimization Based On Magnetic Bacteria Optimization Algorithm

Classification performance of support vector machine (SVM) will be influenced by its model parameters. For this problem, a new method named magnetic bacteria optimization algorithm (MBOA) that optimizes the parameters of SVM is proposed. It is tested by the UCI standard data sets and compared with the other optimization algorithms, such as particle swarm optimization (PSO). Experimental results...

Bus Dispatching Interval Optimization Based on Adaptive Bacteria Foraging Algorithm

The improved bacterial foraging algorithmwas applied in this paper to schedule the bus departing interval. Optimal interval can decrease the total operation cost and passengers’ mean waiting time. The principles of colony sensing, chemotactic action, and improved foraging strategy made this algorithm adaptive. Based on adaptive bacteria foraging algorithm ABFA , a model on one bus line in Hohho...

An Optimization Algorithm Based on Brainstorming Process

In this paper, the human brainstorming process is modeled, based on which two versions of Brain Storm Optimization (BSO) algorithm are introduced. Simulation results show that both BSO algorithms perform reasonably well on ten benchmark functions, which validates the effectiveness and usefulness of the proposed BSO algorithms. Simulation results also show that one of the BSO algorithms, BSO-II,...

Providing an algorithm for solving general optimization problems based on Domino theory

Optimization is a very important process in engineering. Engineers can create better production only if they make use of optimization tools in reduction of its costs including consumption time. Many of the engineering real-word problems are of course non-solvable mathematically (by mathematical programming solvers). Therefore, meta-heuristic optimization algorithms are needed to solve these pro...

An effective optimization algorithm for locally nonconvex Lipschitz functions based on mollifier subgradients