Power scheduling optimization under single-valued neutrosophic uncertainty

Abstract Optimization problems with improper expression of constraints exist widely in practical engineering. In order to achieve a reasonable degree of constraints satisfaction, this paper investigates a single-valued neutrosophic optimization method to deal with system uncertainty. Firstly, an equivalent model based on single-valued neutrosophic entropy is proposed to transform the original problem into a crisp multi-objective optimization problem. The Pareto-front of the optimization problem is then obtained by a multi-objective state transition algorithm. Finally, the best solution is determined by a multi-criteria decision making method. A practical example of a zinc electrowinning process is used to illustrate the effectiveness and advantage of the developed new optimization approach, which provides a more cost-effective solution to decrease the electricity utility charge and satisfy the daily output production requirements.