Evolving chimp optimization algorithm by weighted opposition-based technique and greedy search for multimodal engineering problems

Chimp optimization‐based fuzzy controller for hybrid electric vehicle speed control using electronic throttle plate

“…The following sections explain the four stages of mathematical models of the method adopted by chimpanzees for hunting. [35][36][37]…”

“…For all chaotic maps, the initial value is 0.7. 35 To sum up, ChOA is initiated at the outset by generating an arbitrary chimp population (candidate solutions). In the next stage, all chimps randomly separate into four individual Groups Attacker, barrier, chaser, and driver.…”

“…In summary, it is possible to split the social hunting activity of chimpanzees into two major stages: “exploration,” consisting of walking, blocking, and pursuing, and exploitation of hitting the prey. The following sections explain the four stages of mathematical models of the method adopted by chimpanzees for hunting 35‐37 …”

“…These deterministic systems are potentially also capable of having random actions. For all chaotic maps, the initial value is 0.7 35 …”

“…To address these challenges, nature‐inspired optimization methods can be used to minimize these objective functions. For instance, in 2020, Khishe et al developed chimp optimization (ChOA), 34 which is based on Chimp individual cognition and sexual desire and distinguishes it from other social predator in their community hunting, and it is utilized for nonlinear system controller parameter tuning 35‐37 . Additionally, another population‐oriented optimization approach, mouth flame optimization (MFO), 38 introduced by Mirzali, and its application, 39 and Heap based optimizer, 40 Harris Hawk optimization, 41 are similar to ChOA and used as the methodology for exploration and exploitation in optimization problems for engineering applications.…”