A two warehouse production inventory model is developed for deteriorating items under reliability consideration. The effect of trade credit is considered under inflation. Since, formulating a suitable inventory model is one of the major concerns for an industry, the main objective of this paper is to optimize the total related cost for reliable production process. The model is illustrated through numerical example. The sensitivity analyses of the cost function are performed due to different measures and some managerial inferences are presented.

Traditional economic production quantity (EPQ) model assumes that the production products are perfect. However, this assumption does not hold for many real production systems due to several weaknesses. This paper considers production inventory model with defective items for deteriorating items. In this paper, production rate is considered to be greater than demand rate. Mathematical model is developed for finding optimal order quantity, cycle time and total profit. Moreover, a numerical example is provided to illustrate the proposed model. Next, sensitivity analysis is established to demonstrate the model developed. Finally, some conclusions and future research directions are proposed.

This paper deals with a deterministic inventory model developed for deteriorating items having two separate storage facilities (owned and rented warehouses) due to limited capacity of the existing storage (owned warehouse) with linear time dependent demand (increasing) over a fixed finite time horizon. The model is formulated with infinite replenishment and the successive replenishment cycle lengths are in arithmetic progression. Partially backlogged shortages are allowed. The stocks of rented warehouse (RW) are transported to the owned warehouse (OW) in continuous release pattern. For this purpose, the model is formulated as a constrained non-linear mixed integer programming problem. For solving the problem, an advanced genetic algorithm (GA) has been developed. This advanced GA is based on ranking selection, elitism, whole arithmetic crossover and non-uniform mutation dependent on the age of the population. Our objective is to determine the optimal replenishment number, lot-size of two-warehouses (OW and RW) by maximizing the profit function. The model is illustrated with four numerical examples and sensitivity analyses of the optimal solution are performed with respect to different parameters.

The objective of this study is to develop of an inventory policy for deteriorating items, in which demand for the products is stock dependent and the retailer invests in preservation technology to reduce the rate of product deterioration. In many real-life situations, for certain types of consumer goods, the consumption rate is sometimes influenced by the stock-level. It is usually observed that a large pile of goods on a shelf in a supermarket will lead the customer to buy more and then generate higher demand. The consumption rate may go up or down with the on-hand stock level. This paper is developed with the realistic conditions of demand, allowable credit period, partial backlogging and variable ordering cost. A solution procedure is given to find the optimal preservation technology cost and total cost of the system. A numerical example and sensitivity analysis are presented to illustrate the model.

In general, production system often gets disrupted due to uncertainty and un-planned events, which also affect demands resulting in less abet-margin of a company. With disrupted production system, management would need to study the variation of demand pattern and disruption of system; we have attempted an effort to establish an exponential demand with the production system and solved analytically the problem to determine production time before and after disruptions. Exponentially demand pattern studied, and also we simulate for sensitivity analysis in order to find which parameter is getting significant change for the proposed model.

This paper studies the problem of single machine stochastic scheduling with random processing times, deterministic due dates and an independent setup time. The jobs are also deteriorated based on the position, which their processes are done. The objective function is to find a schedule of jobs, which minimizes the expected value of maximum lateness. A branch and bound scheme is presented to solve the problem analytically and a simulated annealing meta-heuristic (SA) is also provided for solving the problem in larger scales. Computational experiments demonstrate that the proposed SA is capable of finding near optimal solutions with very low gap.

This paper presents a mathematical model for the problem of minimizing the maximum lateness on a single machine when the deteriorated jobs are delivered to each customer in various size batches. In reality, this issue may happen within a supply chain in which delivering goods to customers entails cost. Under such situation, keeping completed jobs to deliver in batches may result in reducing delivery costs. In literature review of batch scheduling, minimizing the maximum lateness is known as NP-Hard problem; therefore the present issue aiming at minimizing the costs of delivering, in addition to the aforementioned objective function, remains an NP-Hard problem. In order to solve the proposed model, a Simulation annealing meta-heuristic is used, where the parameters are calibrated by Taguchi approach and the results are compared to the global optimal values generated by Lingo 10 software. Furthermore, in order to check the efficiency of proposed method to solve larger scales of problem, a lower bound is generated. The results are also analyzed based on the effective factors of the problem. Computational study validates the efficiency and the accuracy of the presented model.

For today’s high competitive market, when immensity purchasing of inventory becomes convenient or obligatory, to discover an alternative market in order to maximize the revenue earned is a tradition. In this paper, we considered an inventory model for seasonal products with Weibull rate of deterioration having two potential markets, say, primary and alternate. To handle the inventory up to the next season will result an increase in total cost. So it is a favorable task to transfer the remaining stock to the alternate market even at a slightly differ in selling price. Solution procedure, numerical examples and sensitivity analysis for different variables are presented to illustrate the model.

The terminal condition of inventory level to be zero at the end of the cycle time adopted by Soni and Shah (2008, 2009) is not viable when demand is stock-dependent. To rectify this assumption, we extend their model for (1) an ending – inventory to be non-zero; (2) limited floor space; (3) a profit maximization model; (4) selling price to be a decision variable, and (5) units in inventory deteriorate at a constant rate. The algorithm is developed to search for the optimal decision policy. The working of the proposed model is supported with a numerical example. Sensitivity analysis is carried out to investigate critical parameters.

This paper deals with an inventory model, which considers the impact of marketing strategies such as pricing and advertising as well as the displayed inventory level on the demand rate of the system. In addition, the demand rate during the stock-out period differs from that during the stock-in period by a function varied on the waiting time up to the beginning of the next cycle. Shortage are allowed and partially backlogged. Here, the deterioration rate is assumed to follow the Weibull distribution. Considering all these factors with others, different scenarios of the system are investigated. To obtain the solutions of these cases and to illustrate the model, an example is considered. Finally, to study the effects of changes of different parameters of the system, sensitivity analyses have been carried out with respect to the different parameters of the system.