Analysis of a fuzzy economic order quantity model for deteriorating items under retailer partial trade credit financing in a supply chain

This paper investigates the economic order quantity (EOQ) — based inventory model for a retailer under two levels of trade credit to reflect the supply chain management situation in the fuzzy sense. It is assumed that the retailer maintains a powerful position and can obtain the full trade credit offered by the supplier yet the retailer just offers a partial trade credit to customers. The demand rate, holding cost, ordering cost, purchasing cost and selling price are taken as fuzzy numbers. Under these conditions, the retailer can obtain the most benefits. Study also investigates the retailer’s inventory policy for deteriorating items in a supply chain management situation as a cost minimization problem in the fuzzy sense. The annual total variable cost for the retailer in fuzzy sense is defuzzified using Graded Mean Integration Representation method. Then the present study shows that the defuzzified annual total variable cost for the retailer is convex, that is, a unique solution exists. Mathematical theorems and algorithms are developed to efficiently determine the optimal inventory policy for the retailer. Numerical examples are given to illustrate the theorems and the algorithms. Finally, the results in this paper generalize some already published results in the crisp sense.     

Retailer’s optimal replenishment and payment policies in the EPQ model under cash discount and two-level trade credit policy

The main purpose of this paper is to investigate the retailer’s optimal cycle time and optimal payment time under the supplier’s cash discount and trade credit policy within the economic production quantity (EPQ) framework. In this paper, we assume that the retailer will provide a full trade credit to his/her good credit customers and request his/her bad credit customers pay for the items as soon as receiving them. Under this assumption, we model the retailer’s inventory system as a cost minimization problem to determine the retailer’s optimal inventory cycle time and optimal payment time under the replenishment rate is finite. Then, an algorithm is established to obtain the optimal strategy. Finally, numerical examples are given to illustrate the theoretical results and obtain some managerial phenomena.     

基于二层信用支付的变质物品库存模型

基于时变需求的库存问题一直是库存管理者关注的重点之一,大多数基于二层信用支付的库存模型都是假设需求率为常数.假设需求率是时间的指数函数,建立了二层信用支付条件下的变质物品库存模型,并证明了最优解是存在且唯一的,给出了确定最优补货策略的算法步骤,最后通过数值例子对主要参数进行了灵敏度分析.     

A class of multiobjective linear programming model with fuzzy random coefficients

The aim of this paper is to deal with a multiobjective linear programming problem with fuzzy random coefficients. Some crisp equivalent models are presented and a traditional algorithm based on an interactive fuzzy satisfying method is proposed to obtain the decision maker’s satisfying solution. In addition, the technique of fuzzy random simulation is adopted to handle general fuzzy random objective functions and fuzzy random constraints which are usually hard to be converted into their crisp equivalents. Furthermore, combined with the techniques of fuzzy random simulation, a genetic algorithm using the compromise approach is designed for solving a fuzzy random multiobjective programming problem. Finally, illustrative examples are given in order to show the application of the proposed models and algorithms.     

关于信用期内含缺陷产品EOQ模型

考虑到在实际中供应链上游供应商提供给下游零售商的信用支付期通常为一个订货周期,建立了缺陷率服从一定分布的缺陷产品在信用支付策略下的最优订货批量模型.模型中允许缺货发生并且以最大期望利润为目标函数,通过分析得到模型最优解.最后给出仿真实验,并且分析了模型参数变化对最优解的影响.     

The optimal pricing and ordering policy for an integrated inventory model when trade credit linked to order quantity

In traditional inventory models, it is implicitly assumed that the buyer must pay for the purchased items as soon as they have been received. However, in many practical situations, the vendor is willing to provide the buyer with a permissible delay period when the buyer’s order quantity exceeds a given threshold. Therefore, to incorporate the concept of vendor–buyer integration and order-size-dependent trade credit, we present a stylized model to determine the optimal strategy for an integrated vendor–buyer inventory system under the condition of trade credit linked to the order quantity, where the demand rate is considered to be a decreasing function of the retail price. By analyzing the total channel profit function, we developed some useful results to characterize the optimal solution and provide an iterative algorithm to find the retail price, buyer’s order quantity, and the numbers of shipment per production run from the vendor to the buyer. Numerical examples and sensitivity analysis are given to illustrate the theoretical results, and some managerial insights are also obtained.     

基于信用支付和现金折扣的变质物品库存模型

本文在供应商提供给零售商定期信用支付和现金折扣情况下,研究了零售商的变质物品最优库存问题。基于信用支付和现金折扣的两种支付条件下,分四种情况建立库存模型,并给出了寻求变质物品最优订购周期和最优付款时间的有效算法。最后,给出算例以及最优解,以说明本模型及求解过程。     

A probability maximization model based on rough approximation and its application to the inventory problem

In the present paper, we concentrate on dealing with a class of multi-objective programming problems with random coefficients and present its application to the multi-item inventory problem. The P-model is proposed to obtain the maximum probability of the objective functions and rough approximation is applied to deal with the feasible set with random parameters. The fuzzy programming technique and genetic algorithm are then applied to solve the crisp programming problem. Finally, the application to Auchan’s inventory system is given in order to show the efficiency of the proposed models and algorithms.     

An inventory model for a deteriorating item with displayed stock dependent demand under fuzzy inflation and time discounting over a random planning horizon

An inventory model for a deteriorating item (seasonal product) with linearly displayed stock dependent demand is developed in imprecise environment (involving both fuzzy and random parameters) under inflation and time value of money. It is assumed that time horizon, i.e., period of business is random and follows exponential distribution with a known mean. The resultant effect of inflation and time value of money is assumed as fuzzy in nature. The particular case, when resultant effect of inflation and time value is crisp in nature, is also analyzed. A genetic algorithm (GA) is developed with roulette wheel selection, arithmetic crossover, random mutation. For crisp inflation effect, the total expected profit for the planning horizon is maximized using the above GA to derive optimal inventory decision. On the other hand when inflationary effect is fuzzy then the above expected profit is fuzzy in nature too. Since optimization of fuzzy objective is not well defined, the optimistic/pessimistic return of the expected profit is obtained using possibility/necessity measure of fuzzy event. Fuzzy simulation process is proposed to determine this optimistic/pessimistic return. Finally a fuzzy simulation based GA is developed and is used to maximize the above optimistic/pessimistic return to get optimal decision. The models are illustrated with some numerical examples and some sensitivity analyses have been presented.     

随机需求下供应链商业信用契约协调

研究一个供应商和一个零售商构成的两级供应链面对随机需求时的商业信用契约协调问题。通过分析商业信用对供应商与零售商各自目标利润及供应链的总利润的影响,建立了商业信用契约协调模型,推导了最优信用期和最优订货量,指出通过信用策略可以使双方实现对利润的合理分配与协调。最后通过数值算例说明了所得结论。     

信用期下时滞变质品供应链库存和定价的Stackelberg均衡策略

在允许缺货和考虑资金机会成本情况下,根据时滞变质品的基本库存模型,分别构建了信用期下供应商为领导者(SL)和零售商为领导者(RL)的Stackelberg博弈模型。通过分析SL和RL下的Stackelberg博弈模型唯一均衡解,得到两个模型中均衡解的解析表达式。最后,根据数值算例分析得出:(1)在SL供应链中信用期并不总使整个供应链协调,然而在RL供应链中信用期的协调效果较好;(2)延长信用期或增加零售价格均能刺激零售商多订货;(3)在两个模型中,零售价格均随变质时刻递增,且整条供应链达到Pareto改进;(4)SL中供应商变动信用期与RL中零售商变动价格相比,SL供应链收益更高;而当信用期和价格固定,其他参数变动时,RL供应链收益更大。     

Stackelberg solutions for fuzzy random two-level linear programming through probability maximization with possibility

This paper considers Stackelberg solutions for decision making problems in hierarchical organizations under fuzzy random environments. Taking into account vagueness of judgments of decision makers, fuzzy goals are introduced into the formulated fuzzy random two-level linear programming problems. On the basis of the possibility and necessity measures that each objective function fulfills the corresponding fuzzy goal, together with the introduction of probability maximization criterion in stochastic programming, we propose new two-level fuzzy random decision making models which maximize the probabilities that the degrees of possibility and necessity are greater than or equal to certain values. Through the proposed models, it is shown that the original two-level linear programming problems with fuzzy random variables can be transformed into deterministic two-level linear fractional programming problems. For the transformed problems, extended concepts of Stackelberg solutions are defined and computational methods are also presented. A numerical example is provided to illustrate the proposed methods.     

Vendor-buyer inventory problem revisited: modeling random yield and trade credit

This paper revisits the vendor-buyer inventory problem considering random yield and trade credit. The problem deals with a single vendor, single buyer setting with deterministic demand and stochastic supply due to the random nature of yield associated with the vendor’s production process. Since a trade credit agreement is in place, the buyer is not required to make a payment to the vendor at the time of delivery of the order. The full payment must be delivered at the end of the trade credit period dictated by the agreement. The problem of interest was originally studied by Chen and Kang (Int J Prod Econ 123(1):52–61, 2010) who treat the delivery frequency, i.e., buyer’s order cycle length, as a decision variable. The current paper demonstrates that the buyer’s order cycle length is in fact a random variable due to the random nature of yield, and there is no guarantee that the trade credit period will be longer or shorter than the buyer’s order cycle length. As a result, the modeling and solution approach presented by Chen and Kang (2010) is flawed. The approach is remedied here by formal application of renewal theory. The exact cost expressions for the vendor-buyer system are redeveloped rigorously. The newly developed expressions are utilized to investigate the optimal decisions under decentralized control. Furthermore, the results are generalized to consider a general distribution of random yield associated with the vendor’s production process. Operational and financial consequences these new and more general results are demonstrated via numerical examples.     

An incentive-compatible solution for trade credit term incorporating default risk

This paper studies the optimal trade credit term decision in an extended economic ordering quantity (EOQ) framework that incorporates a default risk component. A principal-agent bilevel programming model with costs minimization objectives is set up to derive the incentive-compatible credit term. The supplier determines the credit term as the leader in the first level programming, by balancing her/his financing capacity with the retailer’s default risk, order behavior and cost shifting. At the second level, the retailer makes decisions on ordering and payment time by reacting on the term offered by the supplier. A first order condition solution procedure is derived for the bilevel programming when credit term is confined within the practically feasible interval. Two key results are obtained – the condition to derive incentive-compatible credit term, and an equation system to derive threshold default risk criterion filtering retailers suitable for credit granting. Numerical experiments show that the capital cost of the supplier is the most important factor determining the credit term. Default risk acts like a filtering criterion for selecting retailers suitable for credit granting. Empirical evidence supporting our theoretical considerations is obtained by estimating three panel econometric models, using a dataset from China’s listed companies.     

Long-term inventory policy-making through fuzzy decision-making models

The inventory policy, meant as a replenishment rule, has a considerable impact on most firms. The paper considers the determination of optimal inventory policy of firms from a global viewpoint of top management. The inventory is represented as a fuzzy system with the fuzzy inventory level as the output, the fuzzy replenishment as the input and fuzzy demand. The control problem is formulated in terms of decision-making in a fuzzy environment with fuzzy constraints imposed on replenishments, a fuzzy goal for preferable inventory levels to be attained and the fuzzy decision as the intersection of fuzzy constraints and the fuzzy goal at subsequent stages. The planning horizon is infinite. The problem is to find an optimal time-invariant strategy relating the optimal replenishments to the current inventory levels, maximizing the membership function of fuzzy decision. The existence of such a strategy is proved and an algorithm for its determination is given. The optimal time-invariant strategy obtained is represented as a fuzzy conditional statement equated with a fuzzy relation which is the firm's optimal fuzzy replenishment rule.     

The simplified solution algorithm for an integrated supplier-buyer inventory model with two-part trade credit in a supply chain system

Ho et al. [Ho, C.H., Ouyang, L.Y., Su, C.H., 2008. Optimal pricing, shipment and payment policy for an integrated supplier-buyer inventory model with two-part trade credit, European Journal of Operational Research 187, 496-510] discussed the integrated inventory model with two-part trade credit and presented an algorithm to solve it. Basically, Ho et al.’s inventory model is correct and interesting. However, this paper indicates that the solution algorithm described in Ho et al. (2008) can be simplified further. So, this paper can not only derive the optimally closed-form formulations for the optimal numbers of shipments but also develop different algorithms to improve those in Ho et al. (2008). Numerical examples illustrate that the algorithm to locate the optimal solution is rather accurate and rapid.     

The EOQ with defective items and partially permissible delay in payments linked to order quantity derived algebraically

Most researchers established their inventory lot-size models under trade credit financing by assuming that the supplier offers the retailer fully permissible delay in payments and the products received are all non-defective. However, in the real business environment, it often can be observed that the supplier offers the retailer a fully permissible delay in payments only when the order quantity is greater than or equal to the predetermined quantity Q _d . In addition, an arriving order lot usually contains some defective items due to imperfect production processes or other factors. To capture this reality, the paper extends Huang (2007) economic order quantity (EOQ) model with partially permissible delay in payments to consider defective items. We formulate the proposed problem as a profit maximization EOQ model in which the replenishment cycle time is the decision variable. Then we use the arithmetic-geometric mean inequality approach to determine the optimal solution under various situations. An algorithm to obtain the optimal solution is also provided. Finally, the numerical examples and sensitivity analysis are given to illustrate the results.     

A class of multiobjective linear programming models with random rough coefficients

In the present paper, we concentrate on dealing with a class of multiobjective programming problems with random rough coefficients. We first discuss how to turn a constrained model with random rough variables into crisp equivalent models. Then an interactive algorithm which is similar to the interactive fuzzy satisfying method is introduced to obtain the decision maker’s satisfying solution. In addition, the technique of random rough simulation is applied to deal with general random rough objective functions and random rough constraints which are usually hard to convert into their crisp equivalents. Furthermore, combined with the techniques of random rough simulation, a genetic algorithm using the compromise approach is designed for solving a random rough multiobjective programming problem. Finally, illustrative examples are given in order to show the application of the proposed models and algorithms.     

New models for shortest path problem with fuzzy arc lengths

This paper considers the shortest path problem with fuzzy arc lengths. According to different decision criteria, the concepts of expected shortest path, α-shortest path and the most shortest path in fuzzy environment are originally proposed, and three types of models are formulated. In order to solve these models, a hybrid intelligent algorithm integrating simulation and genetic algorithm is provided and some numerous examples are given to illustrate its effectiveness.     

An integrated economic lot-size model for vendor–buyer inventory system when input is random

An integrated strategy is discussed for both vendor and buyer when the input is random. It is shown numerically that the cooperative approach is beneficial to reduce the cost when compared with an independent decision by both the parties. Though the integrated total cost decreases, the buyer’s cost increases due to random input in his inventory. To encourage the buyer to order a large quantity, a trade credit is offered by the vendor to the buyer to settle the account. A conciliation factor is suggested to share the benefits.