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Showing 9 results for Inventory

Valliathal, Uthayakumar,
Volume 2, Issue 2 (6-2011)
Abstract

  We discuss the effects of inflation and time discounting on an EOQ model for deteriorating items under stock-dependent demand and time-dependent partial backlogging. The inventory model is studied under the replenishment policy starting with no shortages. We then use MATLAB to find the optimal replenishment policies. The objective of this model is to maximize the total profit (TP) which includes the sales revenue, purchase cost, the set up cost, holding cost, shortage cost and opportunity cost due to lost sales. Analytical results are given to justify the model. Finally, numerical examples are presented to determine the developed model and the solution procedure. Sensitivity analysis of the optimal solution with respect to major parameters is carried out. We propose a solution procedure to find the solution and obtain some managerial results by using sensitivity analysis.


Anbazhagan, Kumaresan,
Volume 3, Issue 2 (9-2012)
Abstract


Krishnamoorthi,
Volume 4, Issue 1 (5-2013)
Abstract

  A product life cycle is the life span of a product in which the period begins with the initial product specification and ends with the withdrawal from the market of both the product and its support. A product life cycle can be divided into several stages characterized by the revenue generated by the product. This study investigates inventory control policies in a manufacturing system for a single product during the product life cycle, which consists of four stages: introduction, growth, maturity and decline. In all inventory models a general assumption is that products have indefinitely long lives. In general, almost all items deteriorate over time. Often, the rate of deterioration is low and there is little need to consider the deterioration in the determination of the economic lot size. The objective is to derive the cycle time and optimal production lot size to minimize total costs for the product life cycle with deteriorating items. The relevant model is built, solved and some main results on the uniqueness of the solution using rigorous mathematical methods are obtained. Illustrative examples are provided to verify our findings numerically.


R.p. Tripathi, S.m. Mishra,
Volume 4, Issue 2 (10-2013)
Abstract

We develop an inventory model to determine optimal ordering policy under permissible delay in payment by considering demand rate to be stock dependent. Mathematical models are derived under two different cases: credit period being greater than or equal to cycle time for settling the account, and credit period being less than or equal to cycle time for settling the account. The results are illustrated with numerical examples. Sensitivity analysis is given for the proposed model.
N. Shirvani, S. Shadrokh,
Volume 4, Issue 2 (10-2013)
Abstract

We focus on a three-stage supply chain problem for fast moving consumer goods including a supplier, a manufacturer and customers. There are different orders over identical cycles, to be processed in production site. The problem is to find a joint cyclic schedule of raw material procurement and job scheduling minimized the total cost comprised of raw material ordering cost and holding cost, production cost, holding cost of finished products, tardiness cost and rejection cost. An integrated mixed integer programing model is proposed and optimal solution of some instances are provided by solving the model.
Dr Yahia Zare Mehrjerdi, Mitra Moubed,
Volume 6, Issue 1 (3-2015)
Abstract

This paper proposes a robust model for optimizing collaborative reverse supply chains. The primary idea is to develop a collaborative framework that can achieve the best solutions in the uncertain environment. Firstly, we model the exact problem in the form of a mixed integer nonlinear programming. To regard uncertainty, the robust optimization is employed that searches for an optimum answer with nearly all possible deviations in mind. In order to allow the decision maker to vary the protection level, we used the "budget of uncertainty" approach. To solve the np-hard problem, we suggest a hybrid heuristic algorithm combining dynamic programming, ant colony optimization and tabu search. To confirm the performance of the algorithm, two validity tests are done firstly by comparing with the previously solved problems and next by solving a sample problem with more than 900 combinations of parameters and comparing the results with the nominal case. In conclusion, the results of different combinations and prices of robustness are compared and some directions for future researches are suggested finally.


Mr. Hassan Heidari-Fathian, Dr. Seyyed Hamid Reza Pasandideh,
Volume 8, Issue 1 (4-2017)
Abstract

A multi-periodic, multi-echelon green supply chain network consisting of manufacturing plants, potential distribution centers, and customers is developed. The manufacturing plants can provide the products in three modes including production in regular time, production in over time, or by subcontracting. The problem has three objectives including minimization of the total costs of the green supply chain network, maximization of the average safe inventory levels of the manufacturing plants and the distribution centers and minimization of the environmental impacts of the manufacturing plants in producing, holding and dispatching the products and also the environmental impacts of the distribution centers in holding and dispatching the products. The problem is first formulated as a mixed-integer mathematical model. Then, in order to solve the model, the augmented weighted Tchebycheff method is employed and its performance in producing the Pareto optimal solutions is compared with the goal attainment method.
Mr. Mehdi Keramatpour, Prof. Seyed Taghi Akhavan Niaki, Dr. Seyed Hamid Reza Pasandideh,
Volume 9, Issue 2 (6-2018)
Abstract

In this paper, a novel scenario-based two-level inventory control model with a limited budget is formulated. The demand during the selling period is considered to follow a uniform probability distribution. In addition, it is assumed that there will be some customers who are willing to wait for their demands to be satisfied; thus a service level is considered for these customers. The aim is to find the optimal order quantities of the products and the required raw materials such that the relevant expected total profit obtained during the period is maximized. After proving the convexity of the proposed formulation, a penalty function and the Barrier method is proposed to solve the developed nonlinear stochastic programming problem. The problem is solved under different demand scenarios defined in three states of good, fair, and low. Finally, a case study in a dairy manufacturing company is provided to illustrate the application of the proposed methodology in real-world inventory control systems.  

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مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
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