We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Yedek bileşen tahsis probleminde eniyileme: Genetik algoritma ve kesikli olaylı Monte Carlo benzetimi.
- Authors
Şahin, Merve Uzuner; Dengiz, Orhan; Dengiz, Berna
- Abstract
System reliability is one of the performance criteria commonly used in the literature to design and analyze complex engineering systems such as communication networks or server infrastructures and electronic devices. Some of the infrastructure designs that affect industrial processes or even social life are formulated as optimization problems with reliability criteria among the objectives. Such design problems have attracted the attention of many researchers in different disciplines. One commonly studied problem of this group in the literature is the Redundancy Allocation Problem (RAP), which can be defined as the design of a system targeting a high reliability using redundant components in a series-parallel arrangement. The system reliability is obtained with an appropriate method depending on the system characteristics. In this study, a method is proposed for system reliability optimization with a Genetic Algorithm (GA) that uses a Discrete Event Simulation (DES) model to estimate system reliability considering increasing failure and repair rates, reflecting realistic scenarios. The validity of the DES model has been demonstrated on the test problems that are commonly used in the RAP literature. Results show that system designs with higher reliability values at lower costs, where failure and repair scenarios are considered, can be obtained with this realistic approach.
- Subjects
DISCRETE event simulation; RELIABILITY in engineering; MANUFACTURING processes; ENGINEERING systems; TELECOMMUNICATION systems
- Publication
Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi,, 2024, Vol 39, Issue 1, p535
- ISSN
1300-1884
- Publication type
Article
- DOI
10.17341/gazimmfd.1107901