Discrete state transition algorithm for unconstrained integer optimization problems

Xiaojun Zhou, David Yang Gao, Chunhua Yang, Weihua Gui

Abstract: Highlights•A systematic formulation of discrete state transition algorithm is firstly proposed, including the state space representation and five key elements.•A dynamic adjustment strategy called “risk and restoration in probability” is designed to improve the ability to escape from local optima.•The proposed algorithm is successfully integrated with several classical integer optimization problems.