GOOSE Algorithm

The GOOSE algorithm, a new metaheuristic algorithm based on the behaviour of gooses during rest and foraging, was proposed.

The GOOSE algorithm, a new metaheuristic algorithm based on the behavior of goose during rest and foraging, was proposed. The goose balances and stands on one leg to monitor and guard the other birds in the flock. Notably, the GOOSE method is a particle swarm optimization (PSO) -based approach that updates the location of the search agent with the addition of velocity. The GOOSE algorithm is described throughout this work of art along with an explanation of the idea's inspiration.The accuracy and precision of the proposed algorithm were rigorously verified by testing it on various benchmark functions. The GOOSE algorithm was benchmarked on 19 well-known benchmark test functions, and the results were verified through a comparative study with a genetic algorithm (GA), (PSO), dragonfly algorithm (DA), and fitness dependent optimizer (FDO). In addition, the proposed algorithm was tested on ten modern benchmark functions, and the obtained results were compared with three recent algorithms: the dragonfly algorithm, whale optimization algorithm (WOA), and salp swarm algorithm (SSA). Moreover, the GOOSE algorithm was tested on five classical benchmark functions, and the obtained results were evaluated using six algorithms: the fitness dependent optimizer, FOX optimizer, butterfly optimization algorithm (BOA), whale optimization algorithm, dragonfly algorithm, and chimp optimization algorithm (ChOA). The obtained findings attest to the superior performance of the proposed algorithm compared with the other algorithms utilized in the current study. The technique is then used to optimize the welded beam design and Economic Load Dispatch Problem, Pressure Vessel Design Problem, and the Pathological IgG Fraction in the Nervous System, four well-known real-world challenges. The outcomes of engineering case studies illustrate how well the suggested approach can optimize real-world issues.