A novel numerical optimization algorithm inspired from garden balsam

Abstract

This paper introduces a new evolutionary computing method inspired by the seed transmission process of garden balsam. Garden balsam, a beautiful and attractive flower, randomly ejects the seeds within a certain range by virtue of mechanical force originating from cracking of mature seed pods, which is different from natural expansion of most species of plants. The seeds scattered to suitable growth area will have greater reproductive capacity in the next generation, followed by iteration until the most suitable point for growth in a particular space is eventually found. This phenomenon can more intuitively show the process of searching the problem solution space in the optimization problem. The garden balsam optimization algorithm proposed in this paper incorporates two different types of search processes and has a mechanism to maintain population diversity. Through the optimization experiment on 24 constrained optimization problems, the results obtained by using this algorithm are compared with those of some known meta-heuristic search algorithms. The statistical analysis of the experimental results has been implemented by Friedman rank test and Holm-Sidak test. The comparison results verify the effectiveness of the algorithm.

Principal Component Regression Analysis for lncRNA-Disease Association Prediction Based on Pathological Stage Data

“…Because ClGeA correlated global stability area and local incentive area on the basis of the seed cluster, the cluster generated by ClGeA took into account both global stability and local local exploitation [32][33][34]. Besides, it also had good diversity [35][36][37] among clusters. Take 6   = as an example in Figure 2.…”