When solving dynamic multiobjective optimization problems (DMOPs) by evolutionary
algorithms, the historical moving directions of some special points along the Pareto front …

Feature selection problems often appear in the application of data mining, which have been
difficult to handle due to the NP-hard property of these problems. In this study, a simple but …

To solve dynamic multi-objective optimization problems, evolutionary algorithms must be
capable of quickly and accurately tracking the changing Pareto front such that they can …

The state transition algorithm (STA) has been emerging as a novel metaheuristic method for
global optimization over the past few years. In our previous study, the parameter of …

In order to improve the production efficiency and reduce the production cost of copper
removal process (CRP), it is necessary to control the addition rate of zinc powder in CRP. In …

Current paper introduces the iron scrap as a sustainable, economic and efficient reducing
agent for cobalt, nickel, and lithium leaching from waste lithium ion batteries (LIBs). In this …

State transition algorithm (STA) is an efficient and powerful metaheuristic method for solving
global optimization problems, and it has been successfully applied in many engineering …

The goethite process is complicated since its chemical reactions interact with each other,
making its control and optimization in industrial production difficult. The goal of the goethite …

The process industry plays a crucial role in national economic development and national
defense construction. However, as a typical energy-intensive industry, it is at the forefront of …

In this study, a state transition algorithm (STA) is investigated into constrained engineering
design optimization problems. After an analysis of the advantages and disadvantages of two …