Title :
A new meta-heuristic optimization algorithm: Hunting Search
Author :
Oftadeh, R. ; Mahjoob, M.J.
Author_Institution :
Center for Mechatron. & Autom., Univ. of Tehran, Tehran, Iran
Abstract :
A novel optimization algorithm is presented based on group hunting of animals such as lions, wolves, and dolphins. Although these hunters have differences in the way of hunting but they are common in that all of them look for a prey in a group. The hunters encircle the prey and gradually tighten the ring of siege until they catch the prey. Also, each member of the group corrects its position based on its own position and the position of other members. If the prey escapes from the ring, the hunters reorganize the group to siege the prey again. Typical benchmark numerical optimization problems are also presented to demonstrate the effectiveness and robustness of the proposed hunting search (HuS) algorithm. The results indicate that the proposed method is a powerful search and optimization technique. It yields better solutions compared to those obtained using current algorithms when applied to continuous problems.
Keywords :
optimisation; predator-prey systems; search problems; animals; benchmark numerical optimization problems; dolphins; group hunting; hunting search; lions; meta-heuristic optimization algorithm; wolves; Animals; Automation; Dolphins; Evolutionary computation; Humans; Mechanical engineering; Mechatronics; Optimization methods; Robustness; Simulated annealing;
Conference_Titel :
Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, 2009. ICSCCW 2009. Fifth International Conference on
Conference_Location :
Famagusta
Print_ISBN :
978-1-4244-3429-9
Electronic_ISBN :
978-1-4244-3428-2
DOI :
10.1109/ICSCCW.2009.5379451