The K-Means algorithm is the widely used clustering technique. The performance ofthe K-Means algorithm depends highly on original cluster centers and converges to local minima. This paper proposes hybrid Artificial Fish Swarm Means (AFSK-Means) based clustering algorithm, by combining Particle Swarm Optimization with K-Means (PSOK) and Artificial Fish Swarm Algorithm based K-Means (AFSA). The b...

Sinter tumbler strength is an important parameter in the sintering process, and has an important influence on the performance of finished sinter. Artificial fish swarm algorithm have good ability to acquire the global performance, the neural network has strong nonlinear ability and local optimization performance,; AFSA+BP algorithm combined with artificial fish swarm algorithm and BP algorithm,...

Sinter tumbler strength is an important parameter in the sintering process, and has an important influence on the performance of finished sinter. Artificial fish swarm algorithm have good ability to acquire the global performance, the neural network has strong nonlinear ability and local optimization performance,; AFSA+BP algorithm combined with artificial fish swarm algorithm and BP algorithm,...

Supply chain scheduling is the very heartbeat of all supply chain systems. Optimization of the supply chain scheduling can help increase agility while reduce the running cost of corporations. Complying with its structure, supply chain of the networked manufacturing has the characteristics of distributed, multi plants and multi stages. In this paper, a thorough research was first done on the dec...

Artificial fish-swarm algorithm is a realization model of the swarm intelligence optimization algorithm. It uses the optimization model of imitated nature fish for feeding from top to bottom, clusters and rear, local optimization by individual fish, achieve the purpose of global optimal values highlighted in the groups. RBFNN based on the AFSA can accurately find the optimal solution quickly an...

For multi-objective optimization in the QoS routing, this paper combines the artificial fish swarm algorithm and ant colony algorithm and tabu search algorithm, proposes a new improved algorithm, and delves into the application of solving the QoS routing. One main work in this paper is to put forward a mixed algorithm integrating artificial fish swarm and ant colony. Firstly, we randomly genera...

Inspired by the model of artificial fish school algorithm, a novel particle swarm optimizer with the increasing visual of artificial fish is presented after introducing the visual of artificial fish into particle swarm optimization. The neighborhood of each particle is dynamically changed through continually expand the visual of each particle. The local optimal strategy and the global optimal s...

Based on traditional artificial fish swarm algorithm (AFSA), an improved artificial fish swarm algorithm (IAFSA) is proposed and used to solve the problem of optimal operation of cascade reservoirs. To improve the ability of searching the global and the local extremum, the vision and the step of artificial fish are adjusted dynamicly in IAFSA. Moreover, to increase the convergence speed, the th...

In order to overcome the basic glowworm swarm optimization (GSO) algorithm in the high dimension space function optimization effect is poor defects. This paper, we introduce the idea of the traditional complex method, with the complex method the worst part of the glowworm guidance for reflection be good glowworm swarm, so as to continuously make the worst glowworm swarm become the better glowwo...

Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishe...