Research on Task Allocation Method of Mobile Swarm Intelligence Perception Based on Hybrid Artificial Fish Swarm Algorithm

2021 ◽  
pp. 775-785
Author(s):  
Jianjun Li ◽  
Fangyuan Su ◽  
Yu Yang ◽  
Junjun Liu
Keyword(s):  
Swarm Intelligence ◽  
Task Allocation ◽  
Artificial Fish Swarm Algorithm ◽  
Allocation Method ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm

A Novel Approach for Optimization in Dynamic Environments Based on Modified Artificial Fish Swarm Algorithm

2016 ◽  
Vol 15 (02) ◽  
pp. 1650010 ◽  
Author(s):  
Danial Yazdani ◽  
Alireza Sepas-Moghaddam ◽  
Atabak Dehban ◽  
Nuno Horta
Keyword(s):  
Swarm Intelligence ◽  
Optimization Problems ◽  
Dynamic Environments ◽  
Environment Change ◽  
Problem Space ◽  
Artificial Fish Swarm Algorithm ◽  
Novel Approach ◽  
Moving Peaks Benchmark ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm

Swarm intelligence algorithms are amongst the most efficient approaches toward solving optimization problems. Up to now, most of swarm intelligence approaches have been proposed for optimization in static environments. However, numerous real-world problems are dynamic which could not be solved using static approaches. In this paper, a novel approach based on artificial fish swarm algorithm (AFSA) has been proposed for optimization in dynamic environments in which changes in the problem space occur in discrete intervals. The proposed algorithm can quickly find the peaks in the problem space and track them after an environment change. In this algorithm, artificial fish swarms are responsible for finding and tracking peaks and several behaviors and mechanisms are employed to cope with the dynamic environment. Extensive experiments show that the proposed algorithm significantly outperforms previous algorithms in most of tested dynamic environments modeled by moving peaks benchmark.

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

scholarly journals A New Approach to Weapon-Target Assignment in Cooperative Air Combat

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Yi-zhe Chang ◽  
Zhan-wu Li ◽  
Ying-xin Kou ◽  
Qing-peng Sun ◽  
Hai-yan Yang ◽  
...  
Keyword(s):  
Hybrid Algorithm ◽  
Harmony Search ◽  
New Approach ◽  
Artificial Fish Swarm Algorithm ◽  
Target Assignment ◽  
Air Combat ◽  
Improved Harmony Search ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm

A new approach to solving weapon-target assignment (WTA) problem is proposed in this paper. Firstly, relative superiority that lays the foundation for assignment is calculated based on the combat power energy of the fighters. Based on the relative superiority, WTA problem is formulated. Afterwards, a hybrid algorithm consisting of improved artificial fish swarm algorithm (AFSA) and improved harmony search (HS) is introduced and furthermore applied to solve the assignment formulation. Finally, the proposed approach is validated by eight representative benchmark functions and two concrete cooperative air combat examples. The results show that the approach proposed in this paper achieves good performances in solving WTA problem in cooperative air combat.

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