A Concept on Order Quantity at Varying Cost in Variable Rate of Production Situation
Rudresh Pandey1, Shradha Goyal2, Mayank Kumar Pandey3
1Dr. Rudresh Pandey, Professor, Department of Management Studies, ABES Engineering College, Ghaziabad, (U.P), India.
2Dr. Shradha Goyal, Assistant Professor, Jagannath International Management School, (New Delhi), India.
3Mayank Kumar Pandey, Assistant Professor, Department of Management, JIMS Engineering Management Technical Campus, Greater Noida (U.P), India.
Manuscript received on 16 November 2019 | Revised Manuscript received on 04 December 2019 | Manuscript Published on 10 December 2019 | PP: 147-152 | Volume-8 Issue-3S2 October 2019 | Retrieval Number: C10241083S219/2019©BEIESP | DOI: 10.35940/ijrte.C1024.1083S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The concept of EOQ is simply to tackle the management issues of inventory in various types of production systems. This is amongst the most popularly used models in the production houses for inventory. A major issue faced by stock manager is to design an effective policy for replacement, resulting outcome as lowest cost of inventory units. Traditional EOQ theory, assumes majorly two factors that is demand and per unit cost. It is assumed that demand remains constant and can be determined at any level. Secondly that per unit production cost does is not dependent on quantity of order for production. This study is based on a model for stock with multi-item and when per unit cost is dependent on demand and crashing cost of leading time is dependent on lead time. Hence, model has been formulated having constraints of orders and production cost. Unit cost of production is considered fuzzy variable. The jist problem for optimizing the annual total cost has been considered with Karush Kuhn-Tucker conditions method. Mathematical derivations and analysis have been made for one unit, along with testing done from Sensitivity analysis. Illustrations have been taken on random basis.
Keywords: Inventory, Cost, Stock, Demand, Optimization.
Scope of the Article: Production