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A Particle Swarm Optimization for Inventory of Auto Industry Model for Two Warehouses with Deteriorating Items

Journal: International Journal of Trend in Scientific Research and Development (Vol.2, No. 5)

Publication Date:

Authors : ;

Page : 66-74

Keywords : Applied Mathamatics Two-warehouses; deterministic inventory; deteriorating items and Particle Swarm Optimization;

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Abstract

In this Paper Hybrid techniques are the integration of various soft computing techniques that synergizes the strength and weakness of an individual technique with the other therefore the overall performance of such techniques working in unison is increased. A deterministic inventory of Auto industry model has been developed for deteriorating items of Auto industry having a ramp type demand with the effects of inflation with two-storage of Auto industry facilities using Particle Swarm Optimization. Here, we assumed that the inventory of Auto industry holding cost in RW is higher than those in OW. Shortages in inventory of Auto industry are allowed and partially backlogged and it is assumed that the inventory of Auto industry deteriorates over time at a variable deterioration rate using Particle Swarm Optimization. The effect of inflation of Auto industry has also been considered for various costs associated with the inventory of Auto industry system. Cost minimization technique is using Particle Swarm Optimization to get the expressions for total cost and other parameters. Ajay Singh Yadav | Navin Ahlawat | Sharat Sharma"A Particle Swarm Optimization for Inventory of Auto Industry Model for Two Warehouses with Deteriorating Items" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018, URL: http://www.ijtsrd.com/papers/ijtsrd15791.pdf http://www.ijtsrd.com/mathemetics/applied-mathamatics/15791/a-particle-swarm-optimization-for-inventory-of-auto-industry-model-for-two-warehouses-with-deteriorating-items/ajay-singh-yadav

Last modified: 2018-09-26 21:02:32