An optimization of an inventory model of decaying-lot depleted by declining market demand and extended with discretely variable holding costs

Inventory management is considered as major concerns of every organization. In inventory holding, many steps are taken by managers that result a cost involved in this row. This cost may not be constant in nature during time horizon in which perishable stock is held. To investigate on such a case, this study proposes an optimization of inventory model where items deteriorate in stock conditions. To generalize the decaying conditions based on location of warehouse and conditions of storing, the rate of deterioration follows the Weibull distribution function. The demand of fresh item is declining with time exponentially (because no item can always sustain top place in the list of consumers’ choice practically e.g. FMCG). Shortages are allowed and backlogged, partially. Conditions for global optimality and uniqueness of the solutions are derived, separately. The results of some numerical instances are analyzed under various conditions

A two-storage model for deteriorating items with holding cost under inflation and Genetic Algorithms

A deterministic inventory model has been developed for deteriorating items and Genetic Algorithms (GA) having a ramp type demands with the effects of inflation with two-storage facilities. The owned warehouse (OW) has a fixed capacity of W units; the rented warehouse (RW) has unlimited capacity. Here, we assumed that the inventory holding cost in RW is higher than those in OW. Shortages in inventory are allowed and partially backlogged and Genetic Algorithms (GA) it is assumed that the inventory deteriorates over time at a variable deterioration rate. The effect of inflation has also been considered for various costs associated with the inventory system and Genetic Algorithms (GA). Numerical example is also used to study the behaviour of the model. Cost minimization technique is used to get the expressions for total cost and other parameters

DETERIORATING ITEM INVENTORY MODEL WITH SHORTAGES, VARIABLE HOLDING COST AND TIME DEPENDENT QUADRATIC DEMAND: AN OPTIMIZATION APPROACH USING WITH AND WITHOUT CONTROLLABLE RATE OF DETERIORATION

The purpose of this study is to develop time dependent quadratic demand and variable holding cost, a model of inventory system, for instantaneous deteriorating items with the consideration of the facts that the deteriorating rate can be controlled by using the preservation technology (PT). A solution procedure is presented to find the optimal solution of the cost function. Shortages are allowed and partially backlogged. The backlogging rate is assumed to be dependent on the length of the waiting time for the next replenishment. The longer the waiting time is, the smaller the backlogging rate would be. Results have been validated with relevant examples. Sensitivity analysis is performed to show the effect of changes in the parameters on the optimum solution for both the cases that is with and without using the preservation technology respectively. The analysis of the model shows that the solution of the model is quite stable and can be applied for optimizing the inventory cost of deteriorating items for the business enterprise

Effects of inflation and time value of money on an inventory system with deteriorating items and partially backlogged shortages

As the long arm of the grinding, deep financial crisis continues to haunt the global economy, the effects of inflation and time value of money cannot be oblivious to an inventory system. Inflation, defined as a general rise in the prices of goods and services over a period of time, has monetary depreciation as one of its major side effects. And, since inventories correspond to substantial investment in capital for any organization, it would be unethical if the effects of inflation and time value of money are not considered while determining the optimal inventory policy. Moreover, deterioration of items is a phenomenon which cannot be ignored, as it may yield misleading results. Further, under the inflationary conditions, the different cost parameters including the price are bound to vary from cycle to cycle over the planning horizon. Another important factor is shortages which no retailer would prefer, and in practice are partially backlogged and partially lost. In order to convert the lost sales into sales, the retailer offers such customers an incentive, by charging them the price prevailing at the time of placing an order, instead of the current inflated price. Therefore, bearing in mind these facts, the present paper develops an inventory model for a retailer dealing with deteriorating items under inflationary conditions over a fixed planning horizon. The objective is to derive the optimal number of cycles and cycle length that maximizes the net present value of the total profit over a fixed planning horizon. An appropriate algorithm has been proposed to obtain the optimal solution. Finally, a numerical example is provided to illustrate the proposed model. Sensitivity analysis of the optimal solution with respect to major parameters is carried out and some managerial inferences have been presented

Two-warehouse Inventory Model with Multivariate Demand and K-release Rule

AbstractIn this paper, we’ve projected a two-warehouse inventory model for deteriorating things beneath the impact of inflation and continuance of cash, wherever demand follows a rare combination of the linear time variable and on-hand inventory level. In one in the entire warehouse (OW), time-varying linear deterioration was thought-about and within the different (RW) weibull distributed deterioration was studied. Here, shortages were allowed and part backlogged. The stock is transferred from the RW to the OW following a bulk unharness rule. The target here is to seek out the optimum amount to that ought to be ordered and also the optimum variety of cycles during which the number from RW should be transferred to OW to maximize world wide web profit per unit time. The model has additionally been exemplified with the many numerical examples. The results have additionally been understood diagrammatically

A New Multi-objective Inventory Model under Stochastic Conditions with Considering Perishable Costs

This paper presents a new multiple objectives model for the optimal production for an inventory control system. The stocked items may be deteriorates and the systems costs will be change over the time. In the real situation, some but not all customers will wait for backlogged items during a shortage period and therefore, the model incorporates partial backlogging. The demand rate can be a function of inflation and time value of money where the inflation and time horizon i.e., period of business, both are random in nature. The objectives of the problem are: (1) Minimization of the total expected present value of costs over time horizon (consists of the deterioration cost, production cost, inventory holding cost, backordering cost, lost sale cost and ordering cost) and (2) Decreasing the total quantity of goods in the warehouse over time horizon. We propose the ideal point approach to formulate the model. The numerical example has been provided for evaluation and validation of the theoretical results

Optimal Replenishment Policy for Weibull-Distributed Deteriorating Items with Trapezoidal Demand Rate and Partial Backlogging

An inventory model for Weibull-distributed deteriorating items is considered so as to minimize the total cost per unit time in this paper. The model starts with shortage, allowed partial backlogging, and trapezoidal demand rate. By analyzing the model, an efficient solution procedure is proposed to determine the optimal replenishment and the optimal order quantity and the average total costs are also obtained. Finally, numerical examples are provided to illustrate the theoretical results and a sensitivity analysis of the major parameters with respect to the stability of optimal solution is also carried out

A Partial Backlogging Inventory Model for Deteriorating Item under Fuzzy Inflation and Discounting over Random Planning Horizon: A Fuzzy Genetic Algorithm Approach

An inventory model for deteriorating item is considered in a random planning horizon under inflation and time value money. The model is described in two different environments: random and fuzzy random. The proposed model allows stock-dependent consumption rate and shortages with partial backlogging. In the fuzzy stochastic model, possibility chance constraints are used for defuzzification of imprecise expected total profit. Finally, genetic algorithm (GA) and fuzzy simulation-based genetic algorithm (FSGA) are used to make decisions for the above inventory models. The models are illustrated with some numerical data. Sensitivity analysis on expected profit function is also presented. Scope and Purpose. The traditional inventory model considers the ideal case in which depletion of inventory is caused by a constant demand rate. However, to keep sales higher, the inventory level would need to remain high. Of course, this would also result in higher holding or procurement cost. Also, in many real situations, during a longer-shortage period some of the customers may refuse the management. For instance, for fashionable commodities and hightech products with short product life cycle, the willingness for a customer to wait for backlogging is diminishing with the length of the waiting time. Most of the classical inventory models did not take into account the effects of inflation and time value of money. But in the past, the economic situation of most of the countries has changed to such an extent due to large-scale inflation and consequent sharp decline in the purchasing power of money. So, it has not been possible to ignore the effects of inflation and time value of money any more. The purpose of this paper is to maximize the expected profit in the random planning horizon