Frontiers in Engineering Optimization

1983 ◽  
Vol 105 (2) ◽  
pp. 151-154 ◽  
Author(s):  
J. T. Betts
Keyword(s):  
Mathematical Programming ◽  
Engineering Problem ◽  
Theory And Practice ◽  
Programming Algorithm ◽  
Engineering System ◽  
Engineering Optimization ◽  
Complex Engineering ◽  
Optimization Operator

The successful application of a mathematical programming algorithm to a complex engineering problem requires a careful interfacing of needs and requirements between the optimization operator and the engineering system. This paper outlines some areas where interface requirements have not been successfully resolved. In order to bridge the frontier between theory and practice, issues are identified which require resolution by both algorithm developers and system engineers.

An enhanced surrogate-assisted differential evolution for constrained optimization problems

2021 ◽  
Author(s):  
Rafael de Paula Garcia ◽  
Beatriz Souza Leite Pires de Lima ◽  
Afonso Celso de Castro Lemonge ◽  
Breno Pinheiro Jacob
Keyword(s):  
Differential Evolution ◽  
Optimization Problems ◽  
Optimization Procedure ◽  
Nearest Neighbors ◽  
Engineering Optimization ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Constrained Optimization Problems ◽  
Engineering Problems ◽  
Complex Engineering

Abstract The application of Evolutionary Algorithms (EAs) to complex engineering optimization problems may present difficulties as they require many evaluations of the objective functions by computationally expensive simulation procedures. To deal with this issue, surrogate models have been employed to replace those expensive simulations. In this work, a surrogate-assisted evolutionary optimization procedure is proposed. The procedure combines the Differential Evolution method with a Anchor -nearest neighbors ( –NN) similarity-based surrogate model. In this approach, the database that stores the solutions evaluated by the exact model, which are used to approximate new solutions, is managed according to a merit scheme. Constraints are handled by a rank-based technique that builds multiple separate queues based on the values of the objective function and the violation of each constraint. Also, to avoid premature convergence of the method, a strategy that triggers a random reinitialization of the population is considered. The performance of the proposed method is assessed by numerical experiments using 24 constrained benchmark functions and 5 mechanical engineering problems. The results show that the method achieves optimal solutions with a remarkably reduction in the number of function evaluations compared to the literature.

scholarly journals Eco-Innovation by Anticipatory Failure Determination (AFD) Method

2019 ◽  
Vol 1 (1) ◽  
pp. 3271-3280
Author(s):  
Jahau Lewis Chen ◽  
Chuan Hung
Keyword(s):  
Functional Analysis ◽  
Failure Modes ◽  
Public Image ◽  
Engineering System ◽  
Analysis Model ◽  
Innovative Design ◽  
Environmental Consequences ◽  
Model Substance ◽  
Complex Engineering ◽  
Potential Failure

AbstractThis paper presents an eco-innovation method by revised the “Anticipatory Failure Determination (AFD)” method which is the failure analysis tools in TRIZ theory. Using the functional analysis to list the system process and make the functional analysis model. Based on the environmental efficiency factors and functional analysis model, Substance-Field inverse analysis can find a lot of failure modes in the system. In order to assess the priority of risk improvement, the designer can calculate the environmental risk priority number including controlling documents, public image and environmental consequences. Designer can quickly find out the potential failure mode in the complex engineering system with the systematic steps. The TRIZ methods are used for finding eco-innovation idea to solve failure problem. The capability of the whole eco-innovative design process was illustrated by the electrical motorcycle case.

scholarly journals Policy-Engineering Optimization with Visual Representation and Separation-of-Duty Constraints in Attribute-Based Access Control

2020 ◽  
Vol 12 (10) ◽  
pp. 164
Author(s):  
Wei Sun ◽  
Hui Su ◽  
Huacheng Xie
Keyword(s):  
Access Control ◽  
Hamming Distance ◽  
Visual Representation ◽  
Engineering System ◽  
Engineering Optimization ◽  
Efficiency And Effectiveness ◽  
Model Counting ◽  
Separation Of Duty ◽  
Attribute Based Access Control ◽  
Policy Mining

Recently, attribute-based access control (ABAC) has received increasingly more attention and has emerged as the desired access control mechanism for many organizations because of its flexibility and scalability for authorization management, as well as its security policies, such as separation-of-duty constraints and mutually exclusive constraints. Policy-engineering technology is an effective approach for the construction of ABAC systems. However, most conventional methods lack interpretability, and their constructing processes are complex. Furthermore, they do not consider the separation-of-duty constraints. To address these issues in ABAC, this paper proposes a novel method called policy engineering optimization with visual representation and separation of duty constraints (PEO_VR&SOD). First, to enhance interpretability while mining a minimal set of rules, we use the visual technique with Hamming distance to reduce the policy mining scale and present a policy mining algorithm. Second, to verify whether the separation of duty constraints can be satisfied in a constructed policy engineering system, we use the method of SAT-based model counting to reduce the constraints and construct mutually exclusive constraints to implicitly enforce the given separation of duty constraints. The experiments demonstrate the efficiency and effectiveness of the proposed method and show encouraging results.

Using Rio-Paris Flight 447 Crash to Assess Human Error and Failure Propagation Analysis Early in Design

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Lukman Irshad ◽  
H. Onan Demirel ◽  
Irem Y. Tumer ◽  
Guillaume Brat
Keyword(s):  
Human Error ◽  
Prediction Algorithm ◽  
Engineering System ◽  
Human Errors ◽  
System Failures ◽  
Propagation Analysis ◽  
Failure Propagation ◽  
Complex Engineering ◽  
Component Failures ◽  
Complex Engineering System

Abstract While a majority of system vulnerabilities such as performance losses and accidents are attributed to human errors, a closer inspection would reveal that often times the accumulation of unforeseen events that include both component failures and human errors contribute to such system failures. Human error and functional failure reasoning (HEFFR) is a framework to identify potential human errors, functional failures, and their propagation paths early in design so that systems can be designed to be less prone to vulnerabilities. In this paper, the application of HEFFR within the complex engineering system domain is demonstrated through the modeling of the Air France 447 crash. Then, the failure prediction algorithm is validated by comparing the outputs from HEFFR and what happened in the actual crash. Also, two additional fault scenarios are executed within HEFFR and in a commercially available flight simulator separately, and the outcomes are compared as a supplementary validation.

scholarly journals A Dynamic Bayesian Network Structure for Joint Diagnostics and Prognostics of Complex Engineering Systems

Algorithms ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 64
Author(s):  
Austin D. Lewis ◽  
Katrina M. Groth
Keyword(s):  
Health Monitoring ◽  
Power Plants ◽  
Current System ◽  
Dynamic Bayesian Networks ◽  
Diagnostic Model ◽  
Engineering System ◽  
Modeling Framework ◽  
Training Tool ◽  
Future System ◽  
Complex Engineering

Dynamic Bayesian networks (DBNs) represent complex time-dependent causal relationships through the use of conditional probabilities and directed acyclic graph models. DBNs enable the forward and backward inference of system states, diagnosing current system health, and forecasting future system prognosis within the same modeling framework. As a result, there has been growing interest in using DBNs for reliability engineering problems and applications in risk assessment. However, there are open questions about how they can be used to support diagnostics and prognostic health monitoring of a complex engineering system (CES), e.g., power plants, processing facilities and maritime vessels. These systems’ tightly integrated human, hardware, and software components and dynamic operational environments have previously been difficult to model. As part of the growing literature advancing the understanding of how DBNs can be used to improve the risk assessments and health monitoring of CESs, this paper shows the prognostic and diagnostic inference capabilities that are possible to encapsulate within a single DBN model. Using simulated accident sequence data from a model sodium fast nuclear reactor as a case study, a DBN is designed, quantified, and verified based on evidence associated with a transient overpower. The results indicate that a joint prognostic and diagnostic model that is responsive to new system evidence can be generated from operating data to represent CES health. Such a model can therefore serve as another training tool for CES operators to better prepare for accident scenarios.

A mathematical programming algorithm for limit analysis

1991 ◽  
Vol 7 (3) ◽  
pp. 267-274 ◽  
Author(s):  
Zhang Pixin ◽  
Lu Mingwan ◽  
Hwang Kehchih
Keyword(s):  
Mathematical Programming ◽  
Limit Analysis ◽  
Programming Algorithm
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