Numerical Function Optimization Solutions Using the African Buffalo Optimization Algorithm (ABO)
Julius Beneoluchi Odili *
Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Kuantan, Malaysia.
Mohd Nizam Mohmad Kahar
Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Kuantan, Malaysia.
*Author to whom correspondence should be addressed.
Abstract
This paper proposes a new meta-heuristic approach to solving continuous optimization problems using 21 benchmark test cases. The African buffalo algorithm evolved from an understanding of this animal’s survival instincts and the search techniques they utilize in the African forests and savannahs. The African buffalo employs its exceptionally intelligent, cooperative and democratic attitude in its search for the optimal path to pasture. This enables it to get results faster than some other search agents. The African Buffalo Optimization (A.B.O) algorithm simulates the African buffalos’ behaviour by encapsulation in a mathematical model; which solves a number of continuous optimization problems. When compared to the Genetic Algorithm (GA),Chaotic Gray-coded Genetic Algorithm and the Improved Genetic Algorithm (IGA), the results obtained from African Buffalo Optimization show that the algorithm works well and can be extended to solving other optimization problems like: path planning, scheduling, vehicle routing.
Keywords: Numerical function optimization, African buffalo optimization (ABO), global optimization, multimodal, uni-modal