The hotel yield management with two types of room prices,overbooking and cancellations

We consider a problem for hotel room allocations with early discount, cancellations and overbooking. In our model, customers can book a room in discounted price if they reserve before a certain deadline. The model takes overbooking into account. We have expressed the expected total sale function, proved it is unimodal on the number of allocated rooms for early discount and for overbooking, respectively, under a condition and clarified the range where the optimal solution exists. We have derived an optimal allocation for early discount in a specified model without cancellations and overbooking.     

The linear dynamic lot size problem with minimum order quantity

This paper continues the analysis of a special uncapacitated single item lot sizing problem where a minimum order quantity restriction, instead of the setup cost, guarantees a certain level of production lots. A detailed analysis of the model and an investigation of the particularities of the cumulative demand structure allow us to develop a solution algorithm based on the concept of atomic sub-problems. We present an optimal solution to an atomic sub-problem in an explicit form and prove that it serves as a construction block for the optimal solution of the original problem. Computational tests and a comparison with a published algorithm confirm the efficiency of the solution algorithm developed here.     

Optimizing the capital rationing decision with uncertain returns

In this article, we develop a new optimization model for capital rationing with uncertain project returns. Our model maximizes the probability of meeting a predefined target return by selecting a feasible set of projects subject to budget constraints in multiple time periods. We employ a mixed-integer nonlinear algorithm recently developed in the optimization field to solve the resulting nonconvex optimization problem to optimality. Our model and solution methods are tested and validated through a comprehensive computational experiment. Several managerial insights are obtained about the impact of available budget and target return on the optimal solutions. Notably, we have found that increasing target return may not necessarily result in an increase in optimal total expected return of the selected projects. Our model and solution method offer a unified and computationally tractable approach to precisely quantify the tradeoff between project returned and risk.     

详解Excel求解数据包络分析(DEA)

DEA模型自1978年提出,得到了广泛应用,然而其利用的关键在于能否以最简单的方法求到最优解。本文在简要介绍DEA模型的基础上,详尽地以实例阐述了利用EXCEL系统求解DEA模型最优解的步骤过程。     

Optimal pricing and order policies with B2B product returns for fashion products

We study optimal pricing and order policies in supply chain management of fashion products (e.g., a fashion apparel category) with consideration of product returns between supply chain partners (B2B). In order to study channel performance and optimal policies, two stochastic models for centralized channel and decentralized channel are, respectively, developed to handle new fashion and off-season product sales. In the centralized channel, closed-form solutions for optimal order and pricing decisions are proposed for new fashion products. Further, in a decentralized channel, the Stackelberg game model is proposed to derive the optimal Stackelberg equilibrium solution, and then a buy-back contract is designed to coordinate the channel. We also perform parameter analysis on performance of the two channel models. Numerical analysis is finally presented to validate our theoretical results and compare channel performances.     

市场结构范式的标准与构建措施

市场结构理论是整个经济学的构筑要件与基础。在熊彼特淋淳尽致地批驳了完全竞争模式的子虚乌有和容易感染经济萧条的霉菌的特点以后，各种市场结构模式的缺陷暴露无遗，经济研究进入了无所适从的艰难时期，经济实践也陷入了盲人瞎马的混乱局面和夜半临池的危险境地。所以，建设市场结构范式是经济学的当务之急。本文试图通过一系列的反垄断把垄断改造成为市场结构范式。     

Joint pricing and inventory control for non-instantaneous deteriorating items with partial backlogging and time and price dependent demand

In this paper, a joint pricing and inventory control for non-instantaneous deteriorating items is developed. We adopt a price and time dependent demand function. Shortages is allowed and partially backlogged. The major objective is to determine the optimal selling price, the optimal replenishment schedule and the optimal order quantity simultaneously such that, the total profit is maximized. We first show that for any given selling price, optimal replenishment schedule exists and unique. Then, we show that the total profit is a concave function of price. Next, we present a simple algorithm to find the optimal solution. Finally, we solve a numerical example to illustrate the solution procedure and the algorithm.     

Optimal inventory policy with noninstantaneous receipt under trade credit

In the last two decades, the models for inventory replenishment policies under trade credit have been widely studied by several researchers. However, the extant papers only consider the effects of permissible delay in payments in the inventory systems. In some situations, the supplier also may offer a cash discount to encourage retailer to pay for his purchases quickly. On the other hand, an inventory model with instantaneous receipt is not a common feature in actual practice. For generality, this study develops an inventory model with noninstantaneous receipt under trade credit, in which the supplier provides not only a permissible delay but also a cash discount to the retailer. We then characterize the optimal solution and provide an easy-to-use criterion to find the optimal order strategies. Finally, several numerical examples are presented to illustrate the theoretical results.     

Stocking decisions for repairable spare parts pooling in a multi-hub system

This paper presents an analytical model for determining spare parts stocking levels in a single-item, multi-hub, multi-company, repairable inventory system in which complete pooling of stock is permitted among the hubs and companies. The objective is to minimize the total system cost which consists of inventory holding cost, downtime cost and transshipment cost. We develop an approximation method to compute the logistical system performance measures needed for calculating the cost function. To find the optimal stocking levels, a two-stage solution is proposed. In the first stage, the demands at all hubs are aggregated and treated as if occurring at a single location. The optimal number of total spare parts is determined by minimizing the sum of inventory holding cost and downtime cost. In the second stage, a heuristic procedure is developed to find the optimal allocation of the total spare parts to minimize the total transshipment cost.     

A centralized/decentralized design of a full return contract for a risk-free manufacturer and a risk-neutral retailer under partial information sharing

We consider the design of full return contract in a simple supply chain with a risk-free manufacturer and a risk-neutral retailer. In this problem, the ordering quantity and the rebate price for unsold products are determined by the retailer and the manufacturer, respectively. We propose an optimal solution procedure in centralized and decentralized decision making environments considering when the information sharing among the retailer and the manufacturer is partial. We provide numerical examples to explain the proposed solution procedures.     

Integrated inventory model for deteriorating items under a multi-echelon supply chain environment

As the industrial environment becomes more competitive, supply chain management has become essential. The objective of this research is to develop a multi-echelon inventory model for a deteriorating item and to derive an optimal joint total cost from an integrated perspective among the supplier, the producer, and the buyer. A computer code is developed to derive the optimal solution. A numerical example is given to illustrate the model. This paper shows that the integrated approach strategy results in the lowest joint total cost as compared with the independent decision approaches.     

流水工序调度与生产效率的关系模型分析

提出一种基于粒子群算法的流水工序调度任务优化模型。利用流水工序调度任务的特点得到流水工序时间约束条件,利用粒子群算法的原理建立流水工序调度任务优化模型,利用粒子群算法对模型进行求解。仿真实验表明,利用该算法能够得到流水工序调度问题的最优解,提高生产效率。     

三次采油用聚合物黏弹性评价新方法

黏弹性是影响聚合物驱油效率的重要因素。在聚合物常规理化性能检测标准中,没有关于聚合物黏弹性的检测指标。采用CaBER毛细管拉伸断裂流变仪测试聚合物溶液流体丝直径随时间变化曲线,用Exponential模型对曲线进行拟合,拟合的松弛时间可以作为评价聚合物溶液黏弹性大小的技术指标。对水解聚丙烯酰胺、疏水缔合聚合物和高分子表面活性剂的实验研究证明,该评价方法具有样品用量少、操作简便、检测数据重复性高的优点。此外,对采用该方法所适用的聚合物溶液体系及实验条件进行了研究。结果表明:采用聚合物溶液浓度为500mg/L比较合适,在测试前需要对其进行过滤;实验温度应控制在45℃。     

Economic lot-sizing and dynamic quantity competition

We study a problem of dynamic quantity competition in continuous time with two competing retailers facing different replenishment cost structures. Retailer 1 faces fixed ordering costs and variable procurement costs and all inventory kept in stock is subject to holding costs. Retailer 2 only faces variable procurement costs. Both retailers are allowed to change their sales quantities dynamically over time. Following the structure of the economic order quantity (EOQ) model, retailer 1 places replenishment orders in batches and retailer 2 follows a just-in-time (JIT) policy. The objective of both retailers is to maximize their individual average profit anticipating the competitor's replenishment and output decisions. The problem is solved by a two-stage hierarchical optimization approach using backwards induction. The second-stage model is a differential game in output quantities between the two retailers for a given cycle length. At the first stage, the replenishment policy is determined. We prove the existence of a unique optimal solution and derive an open-loop Nash equilibrium. We show that both retailers follow contrary output strategies over the order cycle. The EOQ retailer, driven by inventory holding costs, decreases his market share whereas the output of the JIT retailer increases. Moreover, depending on the cost structure, the EOQ retailer might partially be a monopolist. At the first stage, the EOQ retailer determines the cycle length, anticipating the optimal output trajectories at the second stage.     

Optimal flow-line conditions with worker variability

When classical scheduling theory is applied to task sequencing problems, human characteristics are often not the primary consideration and their impact is often assumed away. In this paper, we examine the workforce scheduling problem in sequential flow line systems. We investigate the impact of within-worker and between-worker variability and discuss the selection of scheduling policies between fixed and work-sharing systems. The methodology includes human performance modeling with the objective to maximize throughput with general results with respect to productivity model. We are interested in determining and characterizing the optimal switching time between workers in work-sharing systems. A closed form solution is established in the case of two and three tasks with two workers. For a general number of workers and tasks we establish the maximum number of changes between assignments. We also establish a bound on throughput. Results allow one to solve workforce scheduling problems reduced complexity given the current set of bounds and conditions.     

Optimal expenditure patterns for risky R&D projects with time-dependent returns

The basic Lucas model for risky R&D projects is revisited. New solutions for optimal expenditures are explored by exploiting the merits of the theory of differential equations. After applying the calculus of variations, a nonlinear differential equation is presented whose solution provides the optimal control for a constant conditional-completion density function and different time-dependent return models. New, exact, and approximate solutions are presented and discussed. It is found, for the class of risky R&D projects under study, that the behavior over time of the optimal expenditure is functionally similar to that of the expected return.     

A Robust Optimization Approach to Capital Rationing and Capital Budgeting

We study the pure capital rationing and the horizon capital budgeting problems using a robust optimization framework. The models and the methodology we propose take into account the uncertainty of the input data. The uncertainty of the cash flows is modeled as a range of values that is allowed for each uncertain data. Unlike stochastic models, this approach does not make assumptions on the probability distribution of uncertain data. Moreover, this approach is highly tractable, easy to implement, and provides insights into portfolio selection problems. An attractive point of the model is that the decision maker can set the value of the parameters that control the robustness of the optimal solution, in order to balance the trade-off between protection level and performance. We illustrate our models with examples that show promising results. We also provide new duality and KKT optimality conditions.     

A local search algorithm for the optimization of the stochastic economic lot scheduling problem

This paper describes a model for the stochastic economic lot scheduling problem (SELSP) and a Local Search heuristic to find close to optimal solutions to this model. The SELSP considers multiple products, which have to be scheduled on a single facility with limited capacity and significant setup times and costs. The demand is modeled as a stationary compound renewal process. The objective is to find a schedule that minimizes the long-run average costs for setups and inventories while satisfying a given fill rate. We use a cyclic scheduling approach in which the individual cycle time of each product is a multiple of some basic period (fundamental cycle).For the deterministic version of the SELSP, efficient heuristics have been developed which guarantee the feasibility of the solution by adding an additional constraint to the problem. In our case this is not sufficient, because for the calculation of the average inventory levels and fill rates we need to develop a schedule with detailed timing of the lots. We present an efficient heuristic for this scheduling problem, which can also be used to check the feasibility of the solution. Thereby, the most time-consuming step (the calculation of average inventory levels and fill rates) is only performed for a limited set of candidates.The algorithm was tested on deterministic benchmark problems from literature and on a large set of stochastic instances. We report on the performance of the heuristic in both cases and try to identify the main factors influencing the objective.     

A dynamic model for the optimization of decoupling point and production planning in a supply chain

In this paper, we propose a dynamic model to simultaneously determine the optimal position of the decoupling point and production-inventory plan in a supply chain such that the total cost of the deviation from the target production rate and the target inventory level is minimized. Using the optimal control theory, we derive the closed form of the optimal solution when the production smoothing policy and the zero-inventory policy are applied. The result indicates that under the production smoothing policy, the overestimation of demand rate during the pre-decoupling stage guarantees the existence of the optimal decoupling point; meanwhile the optimal decoupling point exists under zero-inventory policy when the demand rate is underestimated. Also we perform mathematical analysis on the behavior of the optimal production rate and the inventory level and the effect of problem parameters such as the length of the product life cycle and the forecast error on the performance.