Optimal selling price and lotsize with time varying deterioration and partial backlogging

The article deals with an EOQ (economic order quantity) model over an infinite time horizon for perishable items where demand is price dependent and partial backorder is permitted. The rate of deterioration is taken to be time proportional and it is assumed that shortage occurs at starting of the inventory cycle. Based on the partial backlogging and lost sale cases, the author develops the criterion for the optimal solution for the replenishment schedule, and proves the optimal ordering policy is unique. Moreover, the article suggests to new functions regarding price-dependent demand and time varying deterioration rate. Finally, numerical examples are illustrated to test the model in various issues.     

Integrated inventory models considering permissible delay in payment and variant pricing strategy

The allocation of cost savings is very important for the success of the joint relationship between the buyer and vendor in supply chain management. This paper develops integrated models with permissible delay in payments for determining the optimal replenishment time interval and replenishment frequency. In addition, the variant pricing strategy is employed to obtain both sides’ cost savings in order to entice buyers to join long-term cooperative relationships. A simple solution algorithm is presented to allocate the cost savings in the integration model, and a numerical example is used to demonstrate the feasibility of the proposed integration models.     

A heuristic solution technique to attain the minimal total cost bounds of transporting a homogeneous product with varying demands and supplies

Transportation of a product from multi-source to multi-destination with minimal total transportation cost plays an important role in logistics and supply chain management. Researchers have given considerable attention in minimizing this cost with fixed supply and demand quantities. However, these quantities may vary within a certain range in a period due to the variation of the global economy. So, the concerned parties might be more interested in finding the lower and the upper bounds of the minimal total costs with varying supplies and demands within their respective ranges for proper decision making. This type of transportation problem has received attention of only one researcher, who formulated the problem and solved it by LINGO. We demonstrate that this method fails to obtain the correct upper bound solution always. Then we extend this model to include the inventory costs during transportation and at destinations, as they are interrelated factors. The number of choices of supplies and demands within their respective ranges increases enormously as the number of suppliers and buyers increases. In such a situation, although the lower bound solution can be obtained methodologically, determination of the upper bound solution becomes an NP hard problem. Here we carry out theoretical analyses on developing the lower and the upper bound heuristic solution techniques to the extended model. A comparative study on solutions of small size numerical problems shows promising performance of the current upper bound technique. Another comparative study on results of numerical problems demonstrates the effect of inclusion of the inventory costs.     

Integrated vendor–buyer cooperative inventory models with variant permissible delay in payments

The integrated inventory models usually have the advantage of reducing total cost. However, the way to allocate the cost savings from the integration to the buyer and vendor is critical to the success of the joint relationship between both sides. To deal with this problem, this paper develops the integrated models with the permissible delay in payments for determining the optimal replenishment time interval and replenishment frequency. Applying the models and considering the coefficient of negotiation and the maximum delay payment period, a simple solution algorithm is presented to resolve the allocation of cost savings in the integration model. The coefficient of negotiation is adopted to determine the compromise between the buyer’s and vendor’s cost savings. A numerical example is used to demonstrate the feasibility of the proposed integration models. A sensitivity analysis is also conducted to demonstrate some properties. Using the information from the proposed models, the buyer and vendor can achieve an acceptable compromise solution for both sides in the supply chain management.     

通货膨胀对带有时变需求的变质性物品库存补充策略的影响

本文在考虑通货膨胀的情形下，建立了带有时变需求的变质性物品在有限计划期内的库存补充模型，提供了最优补充次数、最优补充周期长度以及各次补充的最优补充量的一种简单而有效的逼近方法，并用数学例子说明了该方法的实现过程．     

Global solution of bilevel programs with a nonconvex inner program

A bounding algorithm for the global solution of nonlinear bilevel programs involving nonconvex functions in both the inner and outer programs is presented. The algorithm is rigorous and terminates finitely to a point that satisfies ε-optimality in the inner and outer programs. For the lower bounding problem, a relaxed program, containing the constraints of the inner and outer programs augmented by a parametric upper bound to the parametric optimal solution function of the inner program, is solved to global optimality. The optional upper bounding problem is based on probing the solution obtained by the lower bounding procedure. For the case that the inner program satisfies a constraint qualification, an algorithmic heuristic for tighter lower bounds is presented based on the KKT necessary conditions of the inner program. The algorithm is extended to include branching, which is not required for convergence but has potential advantages. Two branching heuristics are described and analyzed. Convergence proofs are provided and numerical results for original test problems and for literature examples are presented.     

考虑通货膨胀与最长顾客等待时间的变质性物品的库存模型

本文建立了一种考虑通货膨胀与时间价值的变质性物品的库存模型,在模型中允许短缺发生且拖后的需求速率与在缺货期间已经发生的缺货量有关.和已有相关模型的主要区别在于本模型把一个可重复的订货周期内的最大平均利润的净现值作为目标函数,且增加了在缺货期间最长顾客等待时间的限制,以确保库存系统拥有较高的服务水平.然后讨论了模型最优解的存在性与唯一性,并提供了寻求模型整体最优解的算法.最后用实例说明了此模型在实际中的应用.     

An efficient optimal solution method for the joint replenishment problem with minimum order quantities

We study the joint replenishment problem (JRP) for M items under deterministic demand, with a minimum order quantity constraint for each item in the replenishment order. We derive bounds on the basic cycle time and we propose an efficient global optimisation procedure to solve the JRP with constraints. Moreover, we also consider the case where a correction is made for empty replenishment occasions. The algorithms are tested with data from a real case and some additional numerical experiments are also presented.     

An Inventory Model for Deteriorating Items with?Two?Levels of Trade Credit Taking Account of Time Discounting

This paper presents an extended inventory model of Huang (J. Oper. Res. Soc. 54, 1011–1015, 2003), which investigated the retailer’s optimal inventory policy under two levels of trade credit. Herein, we consider the impact of a replenishment policy on the timing of the cash flows associated with payments to suppliers and revenue streams from customers. That is, the same cash amount will possess different money value at different future time. To see this, we adopt the more appropriate net present value (NPV) object instead of the average cost objective. In addition, the deteriorating effects will be incorporated in this inventory model, and the time to deterioration of each item follows an exponential distribution. The discounted cash flow (DCF) approach is used to derive the optimal solution in this study. Furthermore, we first show that the optimal solution not only exists bus also is unique. Then, we provide a theorem to locate the optimal ordering policy. Finally, a numerical example for illustration is provided.     

Optimal EOQ Models for Deteriorating Items with Time-Varying Demand

In this paper, optimal inventory lot-sizing models are developed for deteriorating items with general continuous time-varying demand over a finite planning horizon and under three replenishment policies. The deterioration rate is assumed to be a constant fraction of the on-hand inventory. Shortages are permitted and are completely backordered. The proposed solution procedures are shown to generate global minimum replenishment schedules for both general increasing and decreasing demand patterns. An extensive empirical comparison using randomly generated linear and exponential demands revealed that the replenishment policy which starts with shortages in every cycle is the least cost policy and the replenishment policy which prohibits shortages in the last cycle exhibited the best service level effectiveness. An optimal procedure for the same problem with trended inventory subject to a single constraint on the minimum service level (maximum fraction of time the inventory system is out of stock during the planning horizon) is also proposed in this paper.     

Optimal price and lot size determination for a perishable product under conditions of finite production, partial backordering and lost sale

The paper describes an EOQ model of a perishable product for the case of price dependent demand, partial backordering which depends on the length of the waiting time for the next replenishment, and lost sale. The model is solved analytically to obtain the optimal price and size of the replenishment. In the model, the customers are viewed to be impatient and a fraction of the demand is backlogged. This fraction is a function of the waiting time of the customers. In most of the inventory models developed so far, researchers considered that inventory accumulates at the early stage of the inventory and then shortage occurs. This type of inventory is called IFS (inventory followed by shortage) policy. In the present model we consider that shortage occurs before the starting of inventory. We have proved numerically that instead of taking IFS, if we consider SFI (shortage followed by inventory) policy, we would get better result, i.e., a higher profit. The model is extended to the case of non-perishable product also. The optimal solution of the model is illustrated with the help of a numerical example.     

Separate vs. joint replenishment policies with maximum storage requirement costs

Multi-item inventory problems give rise to the possibility of time-phasing the replenishments of different items over the inventory cycle. Such a policy reduces the peak storage requirement, compared to a policy of simultaneous replenishment. This, in turn, increases the amount of warehouse space which is permanently available for leasing throughout the cycle. However, where cost savings may be achieved through combining setups of different items, as in the well known joint replenishment problem, such a time-phasing policy may increase total setup costs. This paper considers the two item joint replenishment problem, where a cost (equivalent to the opportunity cost of warehouse space) attaches to the peak storage requirement which occurs within the inventory cycle. Existing joint replenishment models do not consider such costs, but their consideration suggests that joint replenishment is not always optimal. We analyze possible policies under both joint and separate replenishment, and provide optimal closed form solutions. A numerical example to illustrate the tradeoff between joint and separate replenishment is provided.     

An inventory model of deteriorating items with lot-size dependent replenishment cost and a linear trend in demand

This paper presents an inventory model for deteriorating items over a finite time horizon where the demand increases linearly with time. The method is developed by assuming that the successive replenishment cycle lengths are the same. Many O.R. scientists/researchers obtained an optimal replenishment schedule where the replenishment cost is constant in each cycle length over the finite time horizon. In this paper, we relax the assumption of fixed replenishment cost. The replenishment cost per replenishment is taken to be linearly dependent on the lot-size of that replenishment. Shortages are allowed and are fully backlogged. As a special case, the results for the model without shortages are derived. Finally, two numerical examples are presented to illustrate the model.     

An efficient optimal solution method for the joint replenishment problem

During the last two decades, many heuristic procedures for the joint replenishment problem have appeared in the literature. The only available optimal solution procedure was based on an enumerative approach and was computationally prohibitive. In this paper we present an alternative optimal approach based on global optimisation theory. By applying Lipschitz optimisation one can find a solution with an arbitrarily small deviation from an optimal value. An efficient procedure is presented which uses a dynamic Lipschitz constant and generates a solution in little time. The running time of this procedure grows only linearly in the number of items.     

Two New Heuristic Procedures for the Joint Replenishment Problem

In this paper, we develop two new efficient heuristic procedures for the joint replenishment problem. Each of the two heuristic procedures generates iteratively a near-optimal replenishment policy starting with ordering frequencies that are derived from the solution to a relaxed version of the joint replenishment problem. Both heuristic procedures are illustrated with an example problem involving five jointly ordered items. Seven more illustrative problems, taken from the joint replenishment problem literature, are also solved to assess the cost performance of the two heuristic procedures. They both provide the global optimal replenishment policies for all the illustrative problems.     

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.     

An Optimal Mixed Batch Shipment Policy for Multiple Items in a Single-Supplier Multiple-Retailer Integrated System

This study addresses mixed batch shipment policy with common replenishment cycle for multiple items in a single-supplier multiple-retailer integrated system. The supplier produces multiple items on a single facility under a common replenishment cycle and delivers products to retailer utilizing a mixed batch shipment policy. The objective is to determine the optimal replenishment cycle, the number of shipments, and the structure of mixed shipment, all of which minimize the integrated total cost per unit time. The single-item isolation model is constructed first, and the single-item isolation model is then integrated into the single-item integration model. Moreover, the single-item integration model is integrated into the multi-item integration model. The minimum total cost model is transformed into a maximum replenishment cycle model to optimize the structure of the mixed batch shipment. The replenishment cycle division method is then developed to obtain the optimal solutions to the subject problem. Examples are presented to illustrate the procedures involved in the replenishment cycle division method.     

A study of mixed discrete bilevel programs using semidefinite and semi-infinite programming

In this paper, we study the bilevel programming problem with discrete polynomial lower level problem. We start by transforming the problem into a bilevel problem comprising a semidefinite program (SDP for short) in the lower level problem. Then, we are able to deduce some conditions of existence of solutions for the original problem. After that, we again change the bilevel problem with SDP in the lower level problem into a semi-infinite program. With the aid of the exchange technique, for simple bilevel programs, an algorithm for computing a global optimal solution is suggested, the convergence is shown, and a numerical example is given.     

带非凸二次约束的二次比式和问题的全局优化算法(英文)

对带非凸二次约束的二次比式和问题(P)给出分枝定界算法,首先将问题(P)转化为其等价问题(Q),然后利用线性化技术,建立了(Q)松弛线性规划问题(RLP),通过对(RLP)可行域的细分及求解一系列线性规划问题,不断更新(Q)的上下界,从理论上证明了算法的收敛性,数值实验表明了算法的可行性和有效性.