CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Optimizing Maintenance Activities Using HGA and Monte Carlo Simulation

by Mahadevan ML, Paul Robert T, Vignesh kumar V, Sridhar S
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 21
Year of Publication: 2010
Authors: Mahadevan ML, Paul Robert T, Vignesh kumar V, Sridhar S
10.5120/36-639

Mahadevan ML, Paul Robert T, Vignesh kumar V, Sridhar S . Optimizing Maintenance Activities Using HGA and Monte Carlo Simulation. International Journal of Computer Applications. 1, 21 ( February 2010), 106-110. DOI=10.5120/36-639

@article{ 10.5120/36-639,
author = { Mahadevan ML, Paul Robert T, Vignesh kumar V, Sridhar S },
title = { Optimizing Maintenance Activities Using HGA and Monte Carlo Simulation },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 21 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 106-110 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number21/36-639/ },
doi = { 10.5120/36-639 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:47:40.754925+05:30
%A Mahadevan ML
%A Paul Robert T
%A Vignesh kumar V
%A Sridhar S
%T Optimizing Maintenance Activities Using HGA and Monte Carlo Simulation
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 21
%P 106-110
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The present industrial environment needs proper maintenance for effective functioning of the system underlining the need for an optimal maintenance planning. Maintenance planning is a complex and an inherently stochastic process. This paper presents maintenance planning problem for a process industry. The problem is formulated to determine which of the possible actions viz. maintenance or replacement is to be carried out for the critical components during the planning period. Maintenance is carried out by analyzing improvement in the parameters (viz. MTBF & MTTR) during the design out period. The objective is to minimize the present value of total costs that are incurred by the decision taken during the planning period. The problem is solved by hybrid genetic algorithm (HGA) technique.

References
  1. Akeel Al-Attar, A Hybrid GA-Heuristic Search Strategy. 1994 issue of AI Expert USA. (Sep. 1994), 1-5.
  2. Andal Jayalakshmi, G , Sathiyamoorthy, S, Rajaram, R , A Hybrid Genetic Algorithm- a new approach to solve travelling salesman problem, 1-17.
  3. D E Goldberg. .Genetic Algorithms in Search, Optimization and Machine Learning.. Addison-Wesley, New York, 1989
  4. Husband and Baskar 1982. Optimizing maintenance/production systems" Maintenance management international, 75-81.
  5. Masaya Yoshikawa, Hironori Yamauchi, and Hidekazu Terai, Hybrid Architecture of Genetic Algorithm and Simulated Annealing, Engineering letters, 16:3, EL_16_3_11, 20 August 2008, 1-7.
  6. Michael Andresena , Heidemarie Bräsela , 2008 , Simulated annealing and genetic algorithms for minimizing mean flow time in an open shop, Otto-von-Guericke-Universität, Fakultät für Mathematik, PSF 4120, 39016 Magdeburg, Germany. Press
  7. Pakhira M.K , A Hybrid Genetic Algorithm using Probabilistic Selection, IE (I) Journal, l84, (May 2003), 23-30.
  8. Rajesh Krishnan, Carla C. Purdy, Comparison of Simulated Annealing and Genetic Algorithm approaches in optimizing the output of Biological pathways, 1-8.
  9. Suzannah Yin Wa Wong, 2000, Hybrid simulated annealing/genetic algorithm approach to short-term hydro-thermal scheduling with multiple thermal plants. Department of Computer and Mathemetics, School of Continuing Studies, Chinese University of Hong Kong, 67 Chatham Road South, 13/F, Kowloon, Hong Kong, People's Republic of China.
  10. Tarek M. Mahmoud, A Genetic and Simulated Annealing Based Algorithms for solving the Flow Assignment problem in Computer networks, International Journal of Electronics, Circuits and Systems, 1, 2, 128-134.
  11. Xiangkun MAa, Pingjing YAOa, Xing LUOb and Wilfried ROETZEL, 2007, Synthesis of multi-stream heat exchanger network for multi-period operation with genetic/simulated annealing algorithms, Institute of Thermodynamics, University of the Federal Armed Forces Hamberg, Hamberg D-22039, Germany.
Index Terms

Computer Science
Information Sciences

Keywords

Maintenance planning MTBF MTTR Hybrid Genetic algorithm Optimization

Powered by PhDFocusTM