Abstract
The fruit fly optimization algorithm (FOA) is one of the latest nature-inspired computational models. It has the advantages of having a simple mechanism, fewer control variables, and a fast convergence. However, most applications of the FOA focus on optimization problems in a continuous space. Three-dimensional path planning is a typical discrete optimization problem and can be attributed to multivariable and multiobjective optimization computations. In this paper, we advance an improved FOA model (IFOA) based on engineering techniques. This model is then used to solve for the three-dimensional (3D) path planning of a robot. In a simulation experiment conducted in a virtual three-dimensional space, the IFOA was shown to have a certain capability for three-dimensional path planning. Although the accuracy of the IFOA seems slightly weaker than that of ant colony optimization (ACO), the IFOA may confer time savings of 25% and has greater efficiency. Therefore, this new model still provides a novel and valuable means for solving such discrete optimization problems.
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