The process of intelligent multi-objective parametric optimization design for mirrors is discussed in detail this paper, with the error mirror surface shape and total mass being examined as objectives. establishment complex objective functions solving problem was realized, manual modification model avoided. Moreover, combining a non-dominated sorting genetic algorithm (NSGA) helped Pareto front...

In this article, a new genetic algorithm (GA), called the Nash equilibrium sorting (NESGA,) is introduced to identify equilibria for competitive maximal covering location problem with two and three competitors, which combinatorial game theory where it computationally intractable enumerate all decision options of competitors. Although GAs are widely used in optimization, their applications non-c...

We present a new multiobjective evolutionary algorithm (MOEA), called fast Pareto genetic algorithm (FPGA). FPGA uses a new ranking strategy for the simultaneous optimization of multiple objectives where each solution evaluation is computationally expensive. New genetic operators are employed to enhance the algorithm’s performance in terms of convergence behavior and computational effort. Compu...