Optimization algorithm

Mathematics

Algorithm

Mathematical optimization

Geodesy

Metaheuristic

Multi-swarm optimization

Evolutionary algorithm

Optimization problem

Benchmark (surveying)

Artificial intelligence

Geography

Set (abstract data type)

Programming language

Computer science

Continuous optimization

IEEE Access

In this paper, a new bio-inspired metaheuristic algorithm called Tasmanian Devil Optimization (TDO) is designed that mimics Tasmanian devil behavior in nature. The fundamental inspiration used in TDO is simulation of the feeding behavior of the Tasmanian devil, who has two strategies: attacking live prey or feeding on carrions of dead animals. The proposed TDO is described, then its mathematical modeling is presented. TDO performance in optimization is tested on a set of twenty-three standard objective functions. Unimodal benchmark functions have analyzed the TDO exploitation capability, while high-dimensional multimodal and fixed-exploitation multimodal benchmark functions have challenged the TDO exploration capability. The optimization results indicate the high ability of the proposed TDO in exploration and exploitation and create a proper balance between these two indicators to effectively solve optimization problems. Eight well-known metaheuristic algorithms are employed to analyze the quality of the obtained results from TDO. The simulation results show that the proposed TDO, with its strong performance, has a higher capability than the eight competitor algorithms and is much more competitive. For further analysis, TDO is tested in optimizing four engineering design problems. Implementation results show that TDO has an effective performance in solving real-world applications.

Tasmanian Devil Optimization: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm