CFP last date
20 May 2024
Reseach Article

Analysis of Genetic Algorithm and Particle Swarm Optimization for Warehouse with Supply Chain Management in Inventory Control

by Ajay Singh Yadav, Prerna Maheshwari (Sharma), Anupam Swami
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 154 - Number 5
Year of Publication: 2016
Authors: Ajay Singh Yadav, Prerna Maheshwari (Sharma), Anupam Swami
10.5120/ijca2016912133

Ajay Singh Yadav, Prerna Maheshwari (Sharma), Anupam Swami . Analysis of Genetic Algorithm and Particle Swarm Optimization for Warehouse with Supply Chain Management in Inventory Control. International Journal of Computer Applications. 154, 5 ( Nov 2016), 10-17. DOI=10.5120/ijca2016912133

@article{ 10.5120/ijca2016912133,
author = { Ajay Singh Yadav, Prerna Maheshwari (Sharma), Anupam Swami },
title = { Analysis of Genetic Algorithm and Particle Swarm Optimization for Warehouse with Supply Chain Management in Inventory Control },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2016 },
volume = { 154 },
number = { 5 },
month = { Nov },
year = { 2016 },
issn = { 0975-8887 },
pages = { 10-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume154/number5/26486-2016912133/ },
doi = { 10.5120/ijca2016912133 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:59:24.335979+05:30
%A Ajay Singh Yadav
%A Prerna Maheshwari (Sharma)
%A Anupam Swami
%T Analysis of Genetic Algorithm and Particle Swarm Optimization for Warehouse with Supply Chain Management in Inventory Control
%J International Journal of Computer Applications
%@ 0975-8887
%V 154
%N 5
%P 10-17
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The purpose of the proposed study is to give a new dimension on warehouse with Particle Swarm Optimization and Economic Load Dispatch method using genetic algorithm processes in supply chain in inventory optimization to describe the certain and uncertain market demand which is based on supply reliability and to develop more realistic and more flexible models. we hope that the proposed study has a great potential to solve various practical tribulations related to the warehouse with Particle Swarm Optimization and Economic Load Dispatch method using genetic algorithm processes in supply chain in inventory optimization and also provide a general review for the application of soft computing techniques like genetic algorithms to use for improve the effectiveness and efficiency for various aspect of warehouse with Particle Swarm Optimization and Economic Load Dispatch method control using genetic algorithm.

References
  1. Yimer, A.D. and Demirli, K. (2010) A genetic approach to two-phase optimization of dynamic supply chain scheduling Computers & Industrial Engineering, Volume 58, Issue 3, Pages 411-422.
  2. Taleizadeh, A.A, Niaki, S.T.A. and Barzinpour, F. (2011) Multiple-buyer multiple-vendor multi-product multi-constraint supply chain problem with stochastic demand and variable lead-time: A harmony search algorithm Applied Mathematics and Computation, Volume 217, Issue 22, Pages 9234-9253.
  3. Che, Z.H. and Chiang, C.J. (2010) A modified Pareto genetic algorithm for multi-objective build-to-order supply chain planning with product assembly Advances in Engineering Software, Volume 41, Issues 7–8, Pages 1011-1022.
  4. Changdar, C., Mahapatra, G.S., and Pal, R.K. (2015) An improved genetic algorithm based approach to solve constrained knapsack problem in fuzzy environment Expert Systems with Applications, Volume 42, Issue 4, Pages 2276-2286.
  5. Kannan, G., Sasikumar, P. and Devika, K. (2010) A genetic algorithm approach for solving a closed loop supply chain model: A case of battery recycling Applied Mathematical Modelling, Volume 34, Issue 3, Pages 655-670.
  6. Zhang, H., Deng, Y., Chan, F.T.S. and Zhang, X. (2013) A modified multi-criterion optimization genetic algorithm for order distribution in collaborative supply chain Applied Mathematical Modelling, Volume 37, Issues 14–15, Pages 7855-7864.
  7. Dey, J.K., Mondal, S.K. and Maiti, M. (2008)Two storage inventory problem with dynamic demand and interval valued lead-time over finite time horizon under inflation and time-value of money European Journal of Operational Research, Volume 185, Issue 1,  Pages 170-194.
  8. Jiang, Y., Chen, M. and Zhou, D. (2015) Joint optimization of preventive maintenance and inventory policies for multi-unit systems subject to deteriorating spare part inventory Journal of Manufacturing Systems, Volume 35,  Pages 191-205.
  9. Sourirajan, K., Ozsen, L. and Uzsoy, R. (2009) A genetic algorithm for a single product network design model with lead time and safety stock considerations European Journal of Operational Research, Volume 197, Issue 2, Pages 599-608.
  10. Sarrafha, K., Rahmati, S.H.A., Niaki, S.T.A. and Zaretalab, A. (2015) A bi-objective integrated procurement, production, and distribution problem of a multi-echelon supply chain network design: A new tuned MOEA Computers & Operations Research, Volume 54, Pages 35-51.
  11. Wang, K.J., Makond, B. and Liu, S.Y. (2011) Location and allocation decisions in a two-echelon supply chain with stochastic demand – A genetic-algorithm based solution Expert Systems with Applications, Volume 38, Issue 5, Pages 6125-6131.
  12. Jawahar, N. and Balaji, A.N. (2009) A genetic algorithm for the two-stage supply chain distribution problem associated with a fixed charge European Journal of Operational Research, Volume 194, Issue 2, Pages 496-537.
  13. Jawahar, N. and Balaji, A.N. (2012) A genetic algorithm based heuristic to the multi-period fixed charge distribution problem Applied Soft Computing, Volume 12, Issue 2,  Pages 682-699.
  14. Ramkumar, N., Subramanian, P., Narendran, T.T. and Ganesh, K. (2011) Erratum to “A genetic algorithm approach for solving a closed loop supply chain model: A case of battery recycling” Applied Mathematical Modelling, Volume 35, Issue 12, Pages 5921-5932.
  15. Narmadha, S., Selladurai, V. and Sathish, G. (2010) Multi-Product Inventory Optimization using Uniform Crossover Genetic Algorithm International Journal of Computer Science and Information Security,Vol. 7, No. 1.
  16. Partha Guchhait, Manas Kumar Maiti, Manoranjan Maiti (2010) Multi-item inventory model of breakable items with stock-dependent demand under stock and time dependent breakability rate Computers & Industrial Engineering, Volume 59, Issue 4, Pages 911-920.
  17. Priya, P. and Iyakutti , K. Web based Multi Product Inventory Optimization using Genetic Algorithm International Journal of Computer Applications (0975 – 8887) Volume 25– No.8.
  18. Radhakrishnan, P., Prasad, V.M. and Gopalan, M.R. (2009) Inventory Optimization in Supply Chain Management using Genetic Algorithm International Journal of Computer Science and Network Security, VOL.9 No.1.
  19. Sasan Khalifehzadeh, Mehdi Seifbarghy, Bahman Naderi (2015) A four-echelon supply chain network design with shortage: Mathematical modeling and solution methods Journal of Manufacturing Systems, Volume 35, Pages 164-175.
  20. Pasandideh, S.H.R., Niaki, S.T.A and Yeganeh, J.A (2010) A parameter-tuned genetic algorithm for multi-product economic production quantity model with space constraint, discrete delivery orders and shortages Advances in Engineering Software, Volume 41, Issue 2,  Pages 306-314.
  21. Li, S.H.A., Tserng, H.P., Yin, Y.L.S. and Hsu, C.W (2010) A production modeling with genetic algorithms for a stationary pre-cast supply chain Expert Systems with Applications, Volume 37, Issue 12, Pages 8406-8416.
  22. Singh, S.R. and Kumar, T (2011). Inventory Optimization in Efficient Supply Chain Management International Journal of Computer Applications in Engineering Sciences Vol. 1 Issue 4.
  23. Thakur, L and Desai, A.A. Inventory Analysis Using Genetic Algorithm In Supply Chain Management International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 7.
  24. Wong, W.K., Mok, P.Y. and Leung, S.Y.S. (2013) 8 - Optimizing apparel production systems using genetic algorithms Optimizing Decision Making in the Apparel Supply Chain Using Artificial Intelligence (AI), Pages 153-169.
  25. Yeh, W.C. and Chuang, M.C. (2011) Using multi-objective genetic algorithm for partner selection in green supply chain problems Expert Systems with Applications, Volume 38, Issue 4, Pages 4244-4253.
  26. Ye, Z., Li, Z. and Xie, M. (2010) Some improvements on adaptive genetic algorithms for reliability-related applications Reliability Engineering & System Safety, Volume 95, Issue 2, February 2010, Pages 120-126.
Index Terms

Computer Science
Information Sciences

Keywords

Particle Swarm Optimization genetic algorithm warehouse Supply Chain management Inventory control.