An operational policy for an integrated inventory system under consignment stock policy with controllable lead time and buyers’ space limitation (original) (raw)
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International Journal of Production Research, 2014
This paper studies a vendor-buyer integrated inventory system with buyers' variable demand and warehouse space limitation where the consignment stock (CS) replenishment operates under a controllable lead time. Within any cycle, the production rate, the number of shipments and the shipping size are all fixed. Based upon the CS policy, the vendor agrees to maintain the buyer's inventory to be above a safety level and less than the buyer's space limitation. Due to the uncertainty in the demand, shortages/over stocks are sometimes inevitable. In such cases, penalties are incurred to discourage such occurrence. The holding cost consists of a storage component and a financial component, and the lead time is controlled with an extra investment which is a function of both the shipment size and the reduced time. Two-constraint, five-variable mix-integer optimisation models are established to describe the CS system. Two doublyhybrid meta-heuristic algorithms are employed to solve the models that are complex and difficult to solve with available techniques. Two numerical examples are used to illustrate the solution procedure and the analysis of the computational results reveals the effects of some important parameters used for the annual joint total expected cost of the integrated system. The computational efficiency and quality of the solutions are evaluated by comparing them with other existing and popular methods. The results founds in all comparative evaluation are very encouraging and competitive. first studied the CS policy and stated that it helps the system by simultaneously encouraging the vendor to reduce the batch size and encouraging the buyer to increase its safety stock level. studied a single-vendor single-buyer integrated inventory system under the CS policy and developed a general CS-k model (where k stands for the number of delayed shipments caused by the buyer's space limitation) to decide the optimal ordering quantity that minimises the total cost of the system. They compared the performance of their CS model with that of traditional models and showed that the CS policy might be more preferable under some uncertain environments. Valentini and Zavanella (2003) studied a similar single-vendor single-buyer integrated system from another point of view and provided a way of conducting the performance analysis of the CS policy. At the same period, defined the similar policy as SOI policy and pointed out that the SOI policy can achieve the just-in-time procurement in the buyer without greatly increasing its replenishment cost. They also showed in their numerical examples that the SOI policy outperformed the traditional polices.
A one-vendor multi-buyer integrated production-inventory model: The ‘Consignment Stock’ case
International Journal of Production Economics, 2009
In recent years, companies have strengthened their supply agreements, and even the management of their inventories. To this aim, vendor-managed inventory (VMI) represents an interesting approach to stock monitoring and control, and it has been progressively considered and introduced in several companies. The research proposed investigates the way how a particular VMI policy, known as Consignment Stock (CS), may represent a successful strategy for both the buyer and the supplier.
RAIRO - Operations Research
This paper develops a sustainable integrated inventory model for maximizing profit with a controllable lead time, discrete setup cost reduction, and consideration of environmental issues. Contrary to the available literature, this paper considers a discrete setup cost for the vendor, thus making the integrated model sustainable. The customer’s demand is assumed to be selling-price dependent to increase the number of sales, and the lead time demand follows a Poisson distribution. The integrated model is used to optimized the total shipment number, volume of shipments, safety factor, investments, selling-price, and probability of moving between the “in-control” to “out-of-control” states. An algorithm is developed to obtain the numerical results. Numerical examples and sensitivity analyses are given to illustrate the model.
Applied Mathematical Modelling, 2013
This paper presents an integrated production-inventory model where a vendor produces an item in a batch production environment and supplies it to a set of buyers. The buyer level demand is assumed to be independent normally distributed and lead time of every buyer can be reduced at an added crash cost. The buyers review their inventory using continuous review policy, and the unsatisfied demand at the buyers is completely backordered. A model is formulated to minimize the joint total expected cost of the vendor-buyers system to determine the optimal production-inventory policy. Since it is often difficult to estimate the stock-out cost in inventory systems, and so instead of having stock-out cost component in the objective function, a service level constraint (SLC) corresponding to each buyer is included in the model. A Lagrangian multiplier technique based algorithmic approach is proposed, which evaluates a very limited number of combinations of lead time of the buyers to find simultaneously the optimal lead time, order quantity and safety factor of the buyers and the number of shipments between the vendor and the buyers in a production cycle. Finally, a numerical example and effects of the key parameters are included to illustrate the results of the proposed model.
Solving the vendor-buyer integrated inventory system with arithmetic-geometric inequality
Mathematical and Computer Modelling, 2011
In the past, economic order quantity (EOQ) and economic production quantity (EPQ) were treated independently from the viewpoints of the buyer or the vendor. In most cases, the optimal solution for one player was non-optimal to the other player. In today's competitive markets, close cooperation between the vendor and the buyer is necessary to reduce the joint inventory cost and the response time of the vendor-buyer system. The successful experiences of National Semiconductor, Wal-Mart, and Procter and Gamble have demonstrated that integrating the supply chain has significantly influenced the company's performance and market share [1]). Recently, Yang et al. (2007) [2] presented an inventory model to determine the economic lot size for both the vendor and buyer, and the number of deliveries in an integrated two stage supply chain. In this paper, we present an alternative approach to determine the global optimal inventory policy for the vendor-buyer integrated system using arithmetic-geometric inequality.
International Journal of Production Economics, 2010
This study deals with the order-processing cost reduction and permissible delay in payments problem in the single-vendor single-buyer integrated inventory model. We consider that the order-processing cost can be reduced at an extra crashing cost, which varies with the reduction in the order-processing time length. In addition, the buyer is allowed a fixed time period before they settle the account with the vendor. The objective of this study is to minimize the annual integrated total cost by optimizing simultaneously the delivery interval, the number of deliveries per order and the investment cost in order-processing time. An integrated total cost function is derived, and an algorithm procedure is proposed for determining the optimal decision variables. Finally, numerical examples are provided to illustrate the algorithm procedure.
Glock [2012. Lead time reduction strategies in a single-vendor-single-buyer integrated inventory model with lot size-dependent lead times and stochastic demand. International Journal of Production Economics 136, 37-44] recently presented an integrated inventory model where the lead time can be reduced by crashing the setup and transportation time, by increasing the production rate, or by decreasing the lot size. In this note, we introduce a more realistic lead time crashing cost and propose a modified integrated inventory model by adding the transportation time as a decision variable and assuming that there are two different safety stocks. Furthermore, we give some numerical examples to illustrate the advantages of the modified model.
The Egyptian International Journal of Engineering Sciences and Technology, 2016
Integration of decisions in supply chain management has received increasing consideration recently. The Production-Inventory-Distribution-Routing Problem (PIDRP) is a recent and complex problem that integrates decisions on lot-sizing, inventory management, distribution planning, and vehicle routing problems. In this paper, a generic problem description is given and a Mixed-Integer Programming model (MIP) is proposed to solve the PIDRP, the objective is to minimize the total cost of the combined functions while satisfying the required service levels. The proposed model contributes to the existing literature since it deals with multiple products, split deliveries, a heterogeneous fleet of vehicles, and puts a limit on the duration of the route performed by each vehicle. The proposed model was successfully validated and tested by using small-sized instances from literature. Also, a sensitivity analysis was performed to investigate the effect of estimated parameters on the model results.
An Integrated Vendor and Buyer Inventory Model with Quality Improvement and Setup Cost Reduction
Operations Research and Applications: An International Journal (ORAJ), 2016
This paper attempts to determine optimal production run time and joint capital investment in setup cost reduction and process quality for production system such that the total cost is minimized. We assumed that the setup cost and process quality are logarithmic function. Main focus for this paper is the setup cost reduction. The proposed model is based on the total cost for the single vendor and single buyer. Then, an algorithm procedure is developed in order to find the optimal solution and numerical example is used to demonstrate the benefits of the model. By logarithmic investment function, the optimal investment for process quality and setup cost reduction investment also are obtained. Our objective is to develop an algorithm to determine the order quantity, setup cost, process quality and number of deliveries simultaneously, so that the total cost incurred is minimum.
An integrated inventory model with controllable lead time and distribution-free demand
Applied Stochastic Models in Business and Industry, 2010
The impact of lead time reduction on an integrated periodic review inventory system comprising a single vendor and multiple buyers with a step crashing cost function and service-level constraints is studied. The probability distribution of demand during the protection period for each buyer is unknown, but the mean and the variance are given. Each production lot of the vendor can be delivered in a number of shipments to all buyers. A minimax distribution-free procedure with Lagrange multipliers is applied to determining the lead time, the common shipment cycle time, the target levels of replenishments and the number of shipments per production cycle so that the expected total system cost is minimized. Numerical experiments along with sensitivity analysis were performed to illustrate the effects of parameters on the decision and the total system cost. AN INTEGRATED INVENTORY MODEL 417 lost sales. Moon and Choi [4] pointed out that Ouyang et al. [3] made a mistake by including both the service-level constraint (SLC) and the shortage cost into the model in which both were used redundantly to determine the appropriate level of safety stocks. Hariga [5] developed a stochastic setup cost reduction model with lead time, lot size and setup cost interaction. Chuang et al. [6]