Two infill criteria driven surrogate-assisted multi-objective evolutionary algorithms for computationally expensive problems with medium dimensions

A multi-fidelity surrogate-model-assisted evolutionary algorithm for computationally expensive optimization problems

Integrating data-driven surrogate models and simulation models of di erent accuracies (or delities) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple delities in global optimization is a major challenge. To address it, the two major contrib...

Multiple Objective Evolutionary Algorithms for Independent, Computationally Expensive Objective Evaluations

Evolutionary Optimization of Computationally Expensive Problems via Surrogate Modeling

We present a parallel evolutionary optimization algorithm that leverages surrogate models for solving computationally expensive design problems with general constraints, on a limited computational budget. The essential backbone of our framework is an evolutionary algorithm coupled with a feasible sequential quadratic programming solver in the spirit of Lamarckian learning.We employ a trust-regi...

SOP: parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems

This paper presents a parallel surrogate-based global optimization method for computationally expensive objective functions that is more effective for larger numbers of processors. To reach this goal, we integrated concepts from multi-objective optimization and tabu search into, single objective, surrogate optimization. Our proposed derivative-free algorithm, called SOP, uses non-dominated sort...

Multi-objective Optimization of a Solar Driven Combined Power and Refrigeration System Using Two Evolutionary Algorithms Based on Exergoeconomic Concept

This paper deals with a multi-objective optimization of a novel micro solar driven combined power and ejector refrigeration system (CPER). The system combines an organic Rankine cycle (ORC) with an ejector refrigeration cycle to generate electricity and cold capacity simultaneously. Major thermodynamic parameters, namely turbine inlet temperature, turbine inlet pressure, turbine back pressure, ...