Recent developments in metamodel based robust black-box simulation optimization: An overview

Abstract

In the real world of engineering problems, in order to reduce optimization costs in physical processes, running simulation experiments in the format of computer codes have been conducted. It is desired to improve the validity of simulation-optimization results by attending the source of variability in the model's output(s). Uncertainty can increase complexity and computational costs in Designing and Analyzing of Computer Experiments (DACE). In this state-of the art review paper, a systematic qualitative and quantitative review is implemented among Metamodel Based Robust Simulation Optimization (MBRSO) for black-box and expensive simulation models under uncertainty. This context is focused on the management of uncertainty, particularly based on the Taguchi worldview on robust design and robust optimization methods in the class of dual response methodology when simulation optimization can be handled by surrogates. At the end, while both trends and gaps in the research field are highlighted, some suggestions for future research are directed.

A New Simulation-based Robust Optimal Design of FOPID Controller for Five Bar Linkage Robot in a Cyber-physical System

“…These optimization problems include dynamic and stochastic control system design, sub-communities in machine learning problems, discrete event systems (e.g. queues, operations, and networks), manufacturing, medicine and biology, engineering, computer science, electronics, transportation, and logistics, see [3], [5], [36], [38]- [40]. However, several studies have systematically illustrated the applications of surrogate-based optimization algorithms [36], [37], [41]- [43].…”

“…In this paper, a new outline of robust real-time optimization in the CPS control model under the effect of environmental factors (also known as noise factors or uncertainty, see [4], [5]), and variability in feedback loop due to sensor's anomaly is studied. The main contributions of this study are as following:…”

“…The essential benefit of simulation is its ability to cover complex processes, either deterministic or random, while eliminating mathematical sophistication [2]. Clearly, because of the complexity of mathematical formulation analyzing in many real-world optimization problems, simulation-optimization methods become necessary to find more interest and popularity than other optimization methods [3]- [5].…”

Robust Product Design: A Modern View of Quality Engineering in Manufacturing Systems

“…In addition, levels in this types of factor can be reexamined and reproduced. applicable and useful for modeling a predefined class of problems, see [13], [20].. Figure 6.…”

Robust Product Design: A Modern View of Quality Engineering in Manufacturing Systems

“…Metamodeling is the analysis, construction, and development of the frames, rules, constraints, models, and theories applicable and useful for modeling a predefined class of problems, see [12], [18].. Computation-intensive of design problems is becoming increasingly common in manufacturing industries. Figure 6.…”