Cart (Loading....) | Create Account
Close category search window

Ant colony optimization approach to heterogeneous redundancy in multi-state systems with multi-state components

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Sharma, V.K. ; Dept. of Operational Res., Univ. of Delhi, Delhi, India ; Agarwal, Manju

An algorithm based on ant colony optimization (ACO) has been developed and employed to address the problem of optimum redundancy allocation in series-parallel multi-state systems (MSS) consisting of multi-state components. The objective is to obtain a minimum cost configuration of the system that satisfies the given reliability and weight constraints and the consumer load demand occurring in different operating time intervals. The demand distribution is presented as a piecewise cumulative load curve. The multi-state components are chosen from a list of products available in the market and have their characteristic feeding capacity, reliability, weight and cost. The capacity of the system, thus, strongly depends upon the selection of constituent components. The algorithm allocates heterogeneous redundancy i.e. non-identical components (of maximum two types) are allowed in each subsystem The search of optimal system structure in the ACO algorithm presented in the paper implements a multinomial probability based method to compute exact system reliability index. A penalty function is coupled to handle the constraints and restrict the search near the feasible region. The algorithm is very easy to apply and still obtains very good solutions with promising time efficiency. Two illustrative examples are given to validate the algorithm and to demonstrate its performance.

Published in:

Reliability, Maintainability and Safety, 2009. ICRMS 2009. 8th International Conference on

Date of Conference:

20-24 July 2009

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.