Mi, Yongqiang; Gao, Yuelin Chaotic particle swarm optimization algorithm for nonlinear 0-1 programming problems. (Chinese. English summary) Zbl 1438.90239 Math. Pract. Theory 48, No. 23, 81-88 (2018). Summary: For solving the nonlinear 0-1 programming problems, a chaotic particle swarm optimization algorithm is proposed. The algorithm transformed the nonlinear 0-1 programming problem into unconstrained problem by using penalty function method, the chaos was introduced to initialize the population and increase the diversity, the fitness variance was used to predict whether this algorithm has premature phenomenon. Numerical experiments show that the algorithm is an effective and feasible global optimization algorithm for solving the nonlinear 0-1 programming problem. MSC: 90C09 Boolean programming 90C30 Nonlinear programming 90C59 Approximation methods and heuristics in mathematical programming Keywords:nonlinear 0-1 programming problem; chaos particle swarm optimization; penalty function method; fitness variance PDFBibTeX XMLCite \textit{Y. Mi} and \textit{Y. Gao}, Math. Pract. Theory 48, No. 23, 81--88 (2018; Zbl 1438.90239)