Multi-objective genetic algorithm (GAs) is used for pump design pareto optimization, competing objectives for centrifugal pump design are total head (H), input power (Ps), hydraulic efficiency ( H η ), and input parameter are capacity (Q), and the outer radius of the impeller ( ). Multi-objective presents a set of compromised solution, and provides non-dominated optimal choices for designer. 2 ...

We consider optimization problems whose parameters are known only approximately, based on noisy samples. Of particular interest is the high-dimensional regime, where the number of samples is roughly equal to the dimensionality of the problem, and the noise magnitude may greatly exceed the magnitude of the signal itself. This setup falls far outside the traditional scope of Robust and Stochastic...

This paper introduces a deterministic method for capturing the Pareto front in multi-objective real parameter optimization problems. It is an effort to deal with multi-objective optimization problems that were until now confronted only by stochastic algorithms, specifically evolutionary algorithms. The method is based on a theoretical result that proves the equivalence of non-dominated points t...

In this paper we deal with the semivectorial bilevel problem in the Riemannian setting. The upper level is a scalar optimization problem to be solved by the leader, and the lower level is a multiobjective optimization problem to be solved by several followers acting in a cooperative way inside the greatest coalition and choosing among Pareto solutions with respect to a given ordering cone. For ...

Increasing concerns about energy and emissions from fuel consumption in gas turbines has attracted many researchers to protect the environment and reduce pollutants in the world. The main objective of this paper is to investigate the increasing efficiency of three-stroke gas turbine operation based on the technical analysis of the operation of three-axis gas turbine cycles with non-design condi...