Abstract:

A novel heuristic search algorithm called seeker op-
timization algorithm(SOA)is proposed for the real-parameter
optimization.The proposed SOA is based on simulating the act of
human searching.In the SOA,search direction is based on empir-
ical gradients by evaluating the response to the position changes,
while step length is based on uncertainty reasoning by using a
simple fuzzy rule.The effectiveness of the SOA is evaluated by
using a challenging set of typically complex functions in compari-
son to differential evolution(DE)and three modified particle swarm
optimization(PSO)algorithms.The simulation results show that
the performance of the SOA is superior or comparable to that of
the other algorithms.