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Reseach Article

A Soft computing Optimization based Two Ware-House Inventory Model for Deteriorating Items with shortages using Genetic Algorithm

by Ajay Singh Yadav, Kusum Gupta, Ankur Garg, Anupam Swami
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 126 - Number 13
Year of Publication: 2015
Authors: Ajay Singh Yadav, Kusum Gupta, Ankur Garg, Anupam Swami
10.5120/ijca2015905886

Ajay Singh Yadav, Kusum Gupta, Ankur Garg, Anupam Swami . A Soft computing Optimization based Two Ware-House Inventory Model for Deteriorating Items with shortages using Genetic Algorithm. International Journal of Computer Applications. 126, 13 ( September 2015), 7-16. DOI=10.5120/ijca2015905886

@article{ 10.5120/ijca2015905886,
author = { Ajay Singh Yadav, Kusum Gupta, Ankur Garg, Anupam Swami },
title = { A Soft computing Optimization based Two Ware-House Inventory Model for Deteriorating Items with shortages using Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 126 },
number = { 13 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 7-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume126/number13/22610-2015905886/ },
doi = { 10.5120/ijca2015905886 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:17:20.725120+05:30
%A Ajay Singh Yadav
%A Kusum Gupta
%A Ankur Garg
%A Anupam Swami
%T A Soft computing Optimization based Two Ware-House Inventory Model for Deteriorating Items with shortages using Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 126
%N 13
%P 7-16
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper a two warehouse inventory model for deteriorating items is considered under assumption that the Inventory cost (including holding cost and deterioration cost) in RW (Rented Warehouse) is higher than those in OW (Owned Warehouse) due to better preservation facilities in RW. The demand and holding cost, both are taken variable. Shortages are allowed in the OW and a fraction of shortages backlogged at the next replenishment cycle .This paper mainly dealt with deteriorating items with time dependent demand and variable holding cost which is constant for a definite time period and after that it increases according to length of ordering cycle in RW and remains constant in OW. Transportation cost is taken to be negligible and goods are transported on the basis of bulk release pattern. A genetic algorithm with varying population size is used to solve the model. In this GA a subset of better children is included with the parent population for next generation and size of this subset is a percentage of the size of its parent set. A numerical example is presented to illustrate the model and sensitivity is performed for a parameter keeping rest unchanged.

References
  1. A.K. Bhunia, Ali Akbar Shaikh (2015). An application of PSO in a two-warehouse inventory model for deteriorating item under permissible delay in payment with different inventory policies Applied Mathematics and Computation, Volume 256, Pages 831-850.
  2. A.K. Bhunia, M. Maiti (1998). A two-warehouse inventory model for deteriorating items with a linear trend indemand and shortages, Journal of the Operational Research Society 49, 287-292.
  3. Ajay Singh Yadav, Anupam Swami (2013). A Two-Warehouse Inventory Model for Decaying Items with Exponential Demand and Variable Holding Cost, International Journal of Inventive Engineering and Sciences (IJIES) ISSN: 2319–9598, Volume-1, Issue-5.
  4. Ali Roozbeh Ren Qing-dao-er-ji, Yuping Wang, Xiaoli Wang (2013). Inventory based two-objective job shop scheduling model and its hybrid genetic algorithm Applied Soft Computing, Volume 13, Issue 3, Pages 1400-1406.
  5. Antonio Costa, Giovanni Celano, Sergio Fichera, Enrico Trovato (2010). A new efficient encoding/decoding procedure for the design of a supply chain network with genetic algorithms Computers & Industrial Engineering, Volume 59, Issue 4, Pages 986-999.
  6. Ata Allah Taleizadeh, Seyed Taghi Akhavan Niaki, Mir-Bahador Aryanezhad, Nima Shafii (2013). A hybrid method of fuzzy simulation and genetic algorithm to optimize constrained inventory control systems with stochastic replenishments and fuzzy demand Information Sciences, Volume 220, Pages 425-441.
  7. Bongju Jeong, Ho-Sang Jung, Nam-Kyu Park (2002). A computerized causal forecasting system using genetic algorithms in supply chain management Journal of Systems and Software, Volume 60, Issue 3, Pages 223-237.
  8. David Naso, Michele Surico, Biagio Turchiano, Uzay Kaymak (2007). Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete European Journal of Operational Research, Volume 177, Issue 3, Pages 2069-2099.
  9. Fulya Altiparmak, Mitsuo Gen, Lin Lin, Ismail Karaoglan (2009). A steady-state genetic algorithm for multi-product supply chain network design Computers & Industrial Engineering, Volume 56, Issue 2, Pages 521-537.
  10. Fulya Altiparmak, Mitsuo Gen, Lin Lin, Turan Paksoy (2006). A genetic algorithm approach for multi-objective optimization of supply chain networks Computers & Industrial Engineering, Volume 51, Issue 1, Pages 196-215.
  11. Hertely V. Ronald. (1976). On the EOQ model two levels of storage. Opsearch, 13, 190-196.
  12. Ilkay Saracoglu, Seyda Topaloglu, Timur Keskinturk (2014). A genetic algorithm approach for multi-product multi-period continuous review inventory models Expert Systems with Applications, Volume 41, Issue 18, Pages 8189-8202.
  13. Javad Sadeghi, Seyed Taghi Akhavan Niaki (2015) Two parameter tuned multi-objective evolutionary algorithms for a bi-objective vendor managed inventory model with trapezoidal fuzzy demand Applied Soft Computing, Volume 30, Pages 567-576.
  14. K. D. Rathod and P. H. Bhathawala (2013). Inventory model with inventory-level dependent demand rate, variable holding cost and shortages, International Journal of Scientific & Engineering Research, Volume 4, Issue 8,
  15. K.V.S. Sarma (1987) A deterministic order level inventory model for deteriorating items with two storage facilities. European Journal of Operational Research 29,70-73.
  16. K.V.S. Sarrna (1983). A deterministic inventory model with two level of storage and an optimum release rule, Opsearch 20, 175-180.
  17. M.J. Li, D.S. Chen, S.Y. Cheng, F. Wang, Y. Li, Y. Zhou, J.L. Lang (2010). Optimizing emission inventory for chemical transport models by using genetic algorithm Atmospheric Environment, Volume 44, Issue 32, Pages 3926-3934.
  18. Masao Yokoyama (2002). Integrated optimization of inventory-distribution systems by random local search and a genetic algorithm Computers & Industrial Engineering, Volume 42, Issues 2–4,  Pages 175-188
  19. Maya Gyan, A.K. Pal (2009). A two warehouse Inventory model for deteriorating items with stock dependent demand rate and holding cost,Oper. Res. Int. J.vol(9),153-165.
  20. Miguel Zamarripa, Javier Silvente, Antonio Espuña (2012). Supply Chain Planning under Uncertainty using Genetic Algorithms Computer Aided Chemical Engineering, Volume 30, Pages 457-461.
  21. Nia, Mohammad Hemmati Far, Seyed Taghi Akhavan Niaki (2015). A hybrid genetic and imperialist competitive algorithm for green vendor managed inventory of multi-item multi-constraint EOQ model under shortage Applied Soft Computing, Volume 30,  Pages 353-364.
  22. R.J. Kuo, Y.S. Han (2011). A hybrid of genetic algorithm and particle swarm optimization for solving bi-level linear programming problem – A case study on supply chain model Applied Mathematical Modelling, Volume 35, Issue 8, Pages 3905-3917.
  23. R.K. Gupta, A.K. Bhunia, S.K. Goya (2007). An application of genetic algorithm in a marketing oriented inventory model with interval valued inventory costs and three-component demand rate dependent on displayed stock level Applied Mathematics and Computation, Volume 192, Issue 2, Pages 466-478l.
  24. R.K. Gupta, A.K. Bhunia, S.K. Goyal (2009). An application of Genetic Algorithm in solving an inventory model with advance payment and interval valuedinventory costs Mathematical and Computer Modelling, Volume 49, Issues 5–6, Pages 893-905.
  25. Reza Zanjirani Farahani, Mahsa Elahipana (2008). A genetic algorithm to optimize the total cost and service level for just-in-time distribution in a supply chain International Journal of Production Economics, Volume 111, Issue 2, Pages 229-243
  26. S. Kar. A.K. Bhunia, M. Maiti (2001). Deterministic inventory model with two levels of storage, a linear trendin demand and a fixed time horizon. Computers & Operations Research 28 , 1315-1331.
  27. S.H. Zegordi, I.N. Kamal Abadi, M.A. Beheshti Nia (2010). A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain Computers & Industrial Engineering, Volume 58, Issue 3, Pages 373-381
  28. Salah Alden Ghasimi, Rizauddin Ramli, Nizaroyani Saibani (2014). A genetic algorithm for optimizing defective goods supply chain costs using JIT logistics and each-cycle lengths Applied Mathematical Modelling, Volume 38, Issue 4, Pages 1534-1547
  29. 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.
  30. Seyed Hamid Reza Pasandideh, Seyed Taghi Akhavan Niaki, Ali Roozbeh Nia (2011). A genetic algorithm for vendor managed inventory control system of multi-product multi-constraint economic order quantity model Expert Systems with Applications, Volume 38, Issue 3, Pages 2708-2716.
  31. Seyed Hamid Reza Pasandideh, Seyed Taghi Akhavan Niaki, Nafiseh Tokhmehchi (2011). A parameter-tuned genetic algorithm to optimize two-echelon continuous review inventory systems Expert Systems with Applications, Volume 38, Issue 9, Pages 11708-11714
  32. T.A. Murdeshwar, Y.S. Sathe (1985). Some aspects of lot size model with two levels of storage, Opsearch 22, 255-262.
  33. T.P.M. Pakkala, K.K. Achary (1992). A deterministic inventory model for deteriorating items with twowarehousesand finite replenishment rate, European Journal of Operational Research 57, 157- 167.
  34. Tamás Varga, András Király, János Abonyi (2013). 19 - Improvement of PSO Algorithm by Memory-Based Gradient Search—Application in Inventory Management Swarm Intelligence and Bio-Inspired Computation, Pages 403-422.
Index Terms

Computer Science
Information Sciences

Keywords

Two warehouses Instantaneous deterioration Time-dependent Demand Variable holding cost shortages and Genetic Algorithm