Research on a new optimization algorithm simulating multi- states of matter inspired by finite element analysis approach

A new optimization algorithm is proposed, since a huge problem that many algorithms faced was not being able to effectively balance the global and local search ability. Matter exists in three states: solid, liquid, gas, which presents different motion characteristics. Inspired by multi- states of matter, individuals have characteristics could present The Finite Element Analysis (FEA) approach can simulate be adopted ability algorithm. creative application at field. Artificial Physics Optimization (APO) Gravitational Search Algorithm (GSA) belongs types defined force mass. According FEA approach, node displacement caused stiffness equivalent mass APO GSA. In framework, replaces GSA This paper performs research on two based respectively. are divided into solid state, liquid gas state. effects main parameters performance were studied through experiments 6 static test functions. compared with PSO, basic APO, or for four complex models made up individual, individual iterative process. reasonable model confirmed experimentally. Based model, article conducted complete against Enhancing artificial bee colony multi-elite guidance (MGABC), an adaptive greedy position update strategy (AABC), Multi-strategy ensemble (MEABC), Self-adaptive heterogeneous PSO (fk-PSO), 28 CEC2013 problem. Experimental results show proposed method achieves good comparison its counterparts as consequence better exploration– exploitation balance. supplies improve physics