ITGO: Invasive tumor growth optimization algorithm

摘要: Abstract This paper proposes a new optimization algorithm named ITGO (Invasive Tumor Growth Optimization) based on the principle of invasive tumor growth. The study growth mechanism shows that each cell strives for nutrient in their microenvironment to grow and proliferate. In algorithm, cells were divided into three categories: proliferative cells, quiescent dying cells. movement relies chemotaxis, random walk motion interaction with other different categories. Invasive behaviors are simulated by levy flight through order test effectiveness 50 functions from CEC2005, CEC2008, CEC2010 support vector machine (SVM) parameter problem used compare well-known heuristic methods. Statistical analysis using Friedman Wilcoxon signed-rank statistical Bonferroni–Holm correction demonstrates is better solving global problems comparison meta-heuristic algorithms.