جستجوی مقالات مرتبط با کلیدواژه « Inventory control » در نشریات گروه « صنایع »

The design of the integrated supply chain network plays a vital role in improving the operational efficiency of the company. In this regard, it is essential to integrate strategic issues such as location and transportation management with inventory management strategies in the design of the supply chain network. In the current research, the mathematical model of the three-level supply chain network, including supplier, warehouse, and retailer, has been developed by adopting two coordinated and non-coordinated inventory control strategies. The dynamic adaptive control approach is presented to deal with the uncertainty of the economic order quantity. The study's primary focus is examining the integrity or non-integrity of the inventory of supply chain echelons and its effect on the inventory allocation and the reliability levels of network storage points to guarantee a high level of service. A genetic meta-heuristic algorithm has been used to optimize the problem with an ample search space and provides reasonable solutions and reasonable improvement opportunities. The calculation results show that the amount of inventory and the costs of the entire supply chain network show a significant reduction using the coordinated inventory control strategy.

The classic model of economic order quantity was introduced several decades ago to reduce inventory costs in companies and has since been widely used in various areas of inventory control. In recent years, researchers have developed various aspects of the EOQ model; Because the classic EOQ model does not take into account many important parameters in the real world. The purpose of this paper is to develop a classic EOQ model in order to operationalize and realize the assumptions in the space of simultaneous orders with imperfect quality items.

In this research, a mathematical modeling is developed for the imperfect inventory system as well as the simultaneous ordering requirement. Finally, a numerical example is provided along with the analysis of the results.

The results show that changing the screening rate can have a significant effect on reducing or increasing costs. This cost effect is due to the cost of maintaining items of poor quality until the end of the inspection period. The faster the screening operation and the faster the defective items are removed from the system, the lower the cost.

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In classic models, it is assumed that items of appropriate quality are ordered. In fact, due to the unstable quality of the production process, improper transportation, corruption or other factors, the presence of defective items is inevitable. In the proposed EOQ inventory system, these items are separated by 100% inspection of the consignment, and then these isolated items are sold in a package at a discounted price. Also, in order to reduce the fixed costs of ordering and shipping, the policy of simultaneous ordering has been used for all product categories, which has a high efficiency in reducing costs.

Supply chain management and distribution network design have attracted the attention of many researchers during recent years. This paper addresses a multi-product system of location problem in distribution network that incorporates inventory decisions for each product into capacitated facility location models. In the development of mathematical model, the data of real case study of fast moving consumer goods company is used. A mixed integer nonlinear mathematical programming model is proposed and due to difficulty of obtaining the optimal solution in real-scaled problems, a heuristic solution approach based on Lagrangian relaxation algorithm and sub-gradient method is presented. The proposed solution method is compared with the optimization software on randomly generated test problems with different size. Computational results show that the performance of proposed solution algorithm is very promising in terms of various indexes including 89.1% of DCs capacity, duality gap average and the worst case 1.14% and 3.12% respectively. The results of considered case study also reduced the number of distribution centers from 17 to 12 centers. Finally, some managerial insights are mentioned.

Effective coordination in a supply chain plays a vital role in improving its efficiency. This becomes more critical when it comes to deteriorating materials and products in order to reduce a huge amount of waste or demand fluctuations. Integrated management can effectively reduce the total cost including waste costs, holding costs, shipping, and delivering costs and increase the income, especially when the price or even the demand is affected by the freshness. In this article, an integrated production-inventory system for a perishable product in a two-echelon supply chain, including a producer and multi-retailers, is considered. The quality of raw material and finished product varies at the holding interval and the price is an age-dependent function. Volume discounts are available. The shortage is not allowed. The rates of production and demand are considered determined and fixed. The numbers of deliveries to retailers are not essentially equal. The objective is to determine the number of raw material deliveries to the producer and the number of deliveries from the producer to each retailer in a production cycle in a way that total profit is maximized. This combination of assumptions has not been considered in the literature yet. A nonlinear mixed-integer programming model is developed for the problem. Because of the complexity of the problem, a metaheuristic algorithm is employed to solve the numerical examples. An example is solved and sensitivity analysis is done using a genetic algorithm. The results show that the optimal number of orders and also the economic order sizes change corresponding to the rate of deterioration such that the higher the rate of deterioration, the larger the number of orders and the lower the size of each order. The profit almost increases significantly in the presence of volume discounts in all cases and also increases when a different number of delivers per each cycle for different retailers is possible.

Joint optimal production scheduling and preventive maintenanceare interested in many research andhas a potential impact on the performance of manufacturing systems. In addition, due to the uncertainty in demand, maintenance and inventory shortages are almost inevitable. Therefore, determining the optimal amount of buffer level, the time required to create additional storage space to address the loss, and the maintenance time is a concern for many manufacturers. Paper studied a single-machine production unit with incremental failure rates. The system begins with a h-sized inventory stored in period A and stops as soon as it reaches period m, whichever occurs earlier, and is subject to maintenance. The buffer inventory during this period. A mathematical model and a numerical approach are used to obtain optimal values of variables simultaneously to minimize the average total cost and satisfy the access constraint. The results show that, in the presented model, the total cost and decision variables are highly sensitive to the inventory holding cost but not also for the occurred scenario.

In today's competitive world, decision making for pricing, inventory control policy and lead time, are important challenging issues in non-exclusive markets. The lead time should be determined in a way that inventory of rms, can provide the market demand and also it should not be too long. This study examines the behavior of rms face to variables demand rate depending on selling price, lead time and the inventory level. The model has been extended for a single product in supply chain. Here is assumed that the shortage is not allowed and market demand is a function of the amount of inventory and price of goods sold. This problem is analyzed and mathematically modeled under two scenarios. In the rst scenario the eects of price, lead time and inventory on hand in a single company has been investigated and in the second scenario, the behavior of two competing rms in a non-exclusive market, using the Nash approach is analyzed. Where, both rms, without being informed by each other are competing under a non-cooperative game and each of them is trying to maximize the pro t function. Decisions about the appropriate lead time, selling prices and inventory levels as decision variables of the problem are made so that the rm's pro t is maximized. In numerical examples section, for each of decision variables and parameters of the model, some comparisons have done and the optimal values are obtained. Moreover, sensitive analysis conducted on various parameters of problem. Finally, from sensitivity analysis, we observed that with setting the price elasticity and inventory elasticity of demand, lead time can be managed and maximum pro t is achieved. The results of numerical examples indicate that the maximum pro t for the rms in the second scenario is achieved when the share of both rms, in providing the required inventory of market is equal. From the sensitivity analysis if other parameters are remained constant, when lead time is increased, the inventory levels increases and lead to a prolonged response.

In this research, we develop an economic production quantity model in a three layers supply chain with two different structures. Aforementioned chain composed of a supplier, a manufacturer and multiple retailers. In this chain, the supplier transforms raw material to the semi-finished product and sends them to the manufacturer and then the manufacturer transmutes them to the finished product and delivers to the retailers in order to satisfy market demand. The retailers replenish their inventory at the same time and demand of each retailer is different due to essence of various demand customers and according to the decisions of the chain’s members, two structures of non-integrated and integrated supply chains are surveyed. In this research, we will use the Stackelberg approach to solve the presented models. The ordering cycle of retailers is the decision variable of the model. The main aim of this study is to develop an inventory and production model in three layers supply chains in order to minimize the total cost of chain by utilizing the optimal inventory control policy. At last, numerical examples are presented for each structure of supply chains.

Nowadays, fierce competition in global markets has forced companies to improve the design and management of supply chains, and provide competitive advantages. Decision integrity is one of the main factors which highly lead to a considerable reduction of supply chain costs, and higher costumer’s satisfaction. Distribution network design is based on three major problems: location allocation, vehicle routing and inventory control. Since the effective role of reducing distribution costs in the survival of the supply chain is clear to all, in this paper, these three problems will be incorporated into an integrated model under demand uncertainty. This approach leads to the significant reduction of distribution costs, higher customer satisfaction, and also providing an efficient supply chain. Also in this study, in addition to minimizing the total cost including fixed cost of establishing depots, transportation costs and inventory costs, the customers’ satisfaction will increase by reducing their waiting time. So, a bi-objective mixed integer non-linear model is presented by using chance constrained programming, where customer demands are assumed to have a normal distribution. Then, to solve the model, a hybrid algorithm based on simulated annealing and genetic algorithm is proposed, and is evaluated on a set of instances. The computational results illustrate the algorithm efficiency to solve a wide range of problems with different sizes.

In this research, we investigate the two-echelon singleperiod inventory problem, in which the raw materials and the nal product should be provided at the beginning of the selling period. Raw materials that remain unused and the nal products that remain unsold until the end of the period, can be sold at a discount at the end of the period. the use of coecient in nal products is dierent from each raw material, so the raw materials and the nal product may not have a one-to-one relationship; we have a certain limited budget for buying the raw materials and producing the nal products. Supplier will oer the discount for each raw material to reduce his inventory level, if we buy more than a certain quantity of that raw materials. Since the price of the nal product at the end of the period is so Low, we set a cumulative discount policy to encourage customers for our nal product. Consequently, one of the costumers buys more than a certain quantity, and the price of each nal product for that costumer will be less than the normal price. If the nal product is sold out during the period, depending on the demand, some of our customers will wait for transforming raw materials into the nal product during the period. The objective of this problem is to nd the order of quantities of both the raw materials and the nal product, such that the expected pro t can be maximized. A mathematical model was rst developed for this problem, then a particle swarm optimization algorithm (PSO) was proposed to solve it. Finally, a numerical example was given to illustrate the application of the proposed methodology. This example was solved by the developed PSO algorithm, and to receive a better answer from PSO, we ran the algorithm 50 times.

The traditional economic production quantity (EPQ) model assumes that the production products are all perfect. It is not always true in the real production system, due to imperfect production process or other factors, imperfect quality items maybe produced. Furthermore, it is well-known that the total production-inventory costs can be reduced by reworking the imperfect quality items produced with a relatively smaller additional reworking and holding costs. In addition, the permissible delay in payments offered by the supplier is widely adopted in the practical business market. In this study, we explore the effects of the reworking imperfect quality items and trade credit on the EPQ model with imperfect production processes and complete backlogging. A mathematical model which includes the reworking and shortage costs, interest earned and interest charged is presented. Besides, an arithmetic-geometric mean inequality approach is employed and an algorithm is developed to find the optimal production policy. Furthermore, some numerical examples and sensitivity analysis are provided to demonstrate the proposed model.

In classic inventory control system، purchasing cost must be paid when purchased items are received. Furthermore، in the mentioned models، items may have infinite lifetime، while in the real world، we have some items deteriorate over the time. Also، in order to increase the sales، the suppliers may allow the retailers to pay the purchasing cost some times after receiving the ordered products. Moreover، in the real life cases، the supplier may visit the retailer and send the ordered quantity at random time and the retailer faces to stochastic lead time; then، in this case، the retailer may face to shortage. In this paper، we will extend the periodic inventory control model under delay in payment، stochastic visit interval and partial backordering for a deteriorating item. Under general probability distribution function between replenishment epochs، we show the concavity of the expected profit function and give the condition that must hold for the optimal replenish-up-to-level in order to maximize the profit. In order to show the applicability of the proposed model، the numerical examples and sensitivity analysis are provided.