A Curve Swarm Algorithm for Global Search of State Transition Paths

2015 ◽  
pp. 139-146 ◽  
Author(s):  
Lijuan He ◽  
Yan Wang
Keyword(s):  
State Transition ◽  
Global Search ◽  
Transition Paths ◽  
Swarm Algorithm

The Mathematics of Phenotypic State Transition: Paths and Potential

2020 ◽  
Vol 100 (3) ◽  
pp. 451-464
Author(s):  
Vimalathithan Devaraj ◽  
Biplab Bose
Keyword(s):  
State Transition ◽  
Transition Paths ◽  
Phenotypic State

scholarly journals A Local and Global Search Combined Particle Swarm Optimization Algorithm and Its Convergence Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Weitian Lin ◽  
Zhigang Lian ◽  
Xingsheng Gu ◽  
Bin Jiao
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Global Search ◽  
Fine Tuning ◽  
Particle Swarm Algorithm ◽  
Swarm Optimization ◽  
Large Size ◽  
Swarm Algorithm

Particle swarm optimization algorithm (PSOA) is an advantage optimization tool. However, it has a tendency to get stuck in a near optimal solution especially for middle and large size problems and it is difficult to improve solution accuracy by fine-tuning parameters. According to the insufficiency, this paper researches the local and global search combine particle swarm algorithm (LGSCPSOA), and its convergence and obtains its convergence qualification. At the same time, it is tested with a set of 8 benchmark continuous functions and compared their optimization results with original particle swarm algorithm (OPSOA). Experimental results indicate that the LGSCPSOA improves the search performance especially on the middle and large size benchmark functions significantly.

A Method of Controlled Islanding Strategy Based on Artificial Fish Swarm Algorithm

2014 ◽  
Vol 577 ◽  
pp. 598-602
Author(s):  
Yi Fei Wang ◽  
Fei Tang ◽  
Qing Fen Liao ◽  
Jian Yang
Keyword(s):  
Optimal Strategy ◽  
Optimization Problem ◽  
Mathematic Model ◽  
Global Search ◽  
Artificial Fish Swarm Algorithm ◽  
Controlled Islanding ◽  
Combinational Optimization ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm ◽  
Strategy Searching

Optimal controlled islanding strategy searching is a complex combinational optimization problem. Artificial fish swarm algorithm (AFSA) based on the simulation of fish swarm is an intelligent meta-heuristics. In this paper, AFSA is applied to the searching of optimal controlled islanding strategy. In order to minimize the unbalanced power in each island, a mathematic model is established with some constraints. Simulation result on IEEE-39 node system shows that the proposed method can obtain the optimal strategy promptly and has strong global search ability.

PERFORMANCE EVALUATION OF CULTURAL ARTIFICIAL BEE COLONY AND CULTURAL ARTIFICIAL FISH SWARM ALGORITHM

2019 ◽  
Vol 6 (4) ◽  
pp. 43
Author(s):  
HADIR ADEBIYI BUSAYO ◽  
TIJANI SALAWUDEEN AHMED ◽  
FOLASHADE O. ADEBIYI RISIKAT ◽  
◽  
◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Artificial Bee Colony ◽  
Artificial Fish Swarm Algorithm ◽  
Bee Colony ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm
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