RESUMO
This paper presents an investigation of four metaheuristics for multimodal
optimization. The algorithms have been implemented in
R and compared against each other using well-known benchmark
functions. We implemented the following algorithms: Genetic Algorithm
(GA), Particle Swarm Optimization (PSO), Differential Evolution
(DE), and Bat Algorithm (BA). For comparisons, we used five
multimodal benchmarks: Rosenbrock, Griewank, Ackley, Schwefel,
and Alpine. Preliminary results show that Bat Algorithm and Genetic
Algorithm tend to discover the best solution considering the
parameters that have been set up.