The impact of customer returns on pricing and order decisions

In this paper, we address the simultaneous determination of price and inventory replenishment when customers return product to the firm. We examine cases when the quantity of returned product is a function of both the quantity sold and the price, in single and multi-period problems, with and without uncertainty in demand.     

滑雪场季卡定价促销模型研究

根据06~07年间全国主要滑雪场的门市价和季卡价,首先运用EVIEWS6计量软件做出散点图、残差分析图以及残差的自相关-偏相关图,然后运用最小二乘估计方法确定回归方程系数,建立回归和序列组合模型,并将滑雪场的门市价代入相应方程计算出季卡付费方式下滑雪场应制定的最优价格,最后做相应的误差分析并总结本文模型的优点与不足.     

Reinsurance contract design when the insurer is ambiguity-averse

This paper investigates proportional and excess-loss reinsurance contracts in a continuous-time principal–agent framework, in which the insurer is the agent and the reinsurer is the principal. Insurance claims follow the classic Cramér–Lundberg process. The insurer believes that the claim intensity is uncertain and he chooses robust risk retention levels to maximize the penalty-dependent multiple-priors utility. The reinsurer designs reinsurance contracts subject to the insurer’s incentive compatibility constraints. The analytical expressions of the two robust reinsurance contracts are derived. Our results show that the robust reinsurance demand and price are greater than their respective standard values without model ambiguity, and increase as the insurer’s ambiguity aversion increases. Moreover, the reinsurer specifies a decreasing reinsurance price to induce increasing demand over time. Specifically, the price of excess-loss reinsurance is higher, relative to that of proportional reinsurance. Further, only if the insurer’s risk aversion is high or the reinsurer’s risk aversion is low, the insurer prefers the excess-loss reinsurance contract.     

A column generation approach for location-routing problems with pickup and delivery

In this paper we formulate an integer programming model for the Location and Routing Problem with Pickup and Delivery. We propose a column generation scheme and implement, for the subproblem, a label-setting algorithm for the shortest path with pickup and delivery and time windows problem. We also propose a set of heuristics to speed up this process. To validate the model, we implement the column generation scheme and test it on different instances developed in this paper. We also provide an analysis of how the costs of opening depots and the fixed cost of routes affect the optimal solution.     

考虑预付定金和退货的SMPEs产品定价与优化策略

借鉴中小制造型企业(SMPEs)在线渠道预售模式,考虑市场中存在预付订金和不预付订金的顾客,并将其退货情况引入到生产商利润表达式中,构建确定性和随机性市场需求下的SMPEs产品销售利润最大化模型,推导生产商产品最优定价的解析解;对比两种销售模式的利润,得到了生产商选择不同销售策略的条件。进一步考虑预付定金的产品数量、预交定金比例、退货数量是关于价格折扣敏感的情况,采用拉格朗日乘子法对生产商产品定价及优化问题进行研究,分析求得生产商销售策略(产品定价和价格折扣)的近似最优解。最后,通过数值算例对研究结论进行了验证并给出经济学解释。     

On fail‐safe systems under random shocks

In practical situations, systems often suffer shocks from external stressing environments, stressing the system at random. These random shocks may have non‐ignorable effects on the system's reliability. In this paper, we provide sufficient (and necessary) conditions on components' lifetimes and their surviving probabilities from random shocks for comparing the lifetimes of two fail‐safe systems by means of the usual stochastic, hazard rate, and likelihood ratio orderings. Numerical examples are presented to highlight these theoretical results as well.     

专业零售商与厂家直售商的多渠道供应价格博弈的混沌动力学研究

在零售市场,专业零售商与厂家直售商的价格竞争日益突起,再次背景下构建了专业零售商和厂家直售商组成的多渠道供应链价格博弈模型。利用管理学、经济学以及混沌动力学有关理论,对多渠道供应链中各渠道间长期价格博弈的动态演化过程进行理论验证和数据仿真,研究了专业零售商和厂家直售商的价格决策变量的变化给市场带来的影响。研究表明,双方价格决策变量的不断增加,市场从稳定进入混沌无序状态。采用调整参数可以对混沌进行有效的控制,研究结果具有较好的理论和实际应用价值。     

An EOQ model for perishable products with discounted selling price and stock dependent demand

A single item economic order quantity model is considered in which the demand is stock dependent. After a certain time the product starts to deteriorate and due to visualization effect and other aspects of deterioration the demand becomes constant. In that situation a discount on selling price provides significant increment in demand rate. In this paper we investigate how much discount on selling price may be given during deterioration to maximize the profit per unit time and whether a pre-deterioration discount affects the unit profit or not. A mathematical model is developed incorporating both pre- and post deterioration discounts on unit selling price, where analytical results reveal some important characteristics of discount structure. A numerical example is presented and sensitivity analysis of the model is carried out.     

Heavy-tails and regime-switching in electricity prices

In this paper we first analyze the stylized facts of electricity prices, in particular, the extreme volatility and price spikes which lead to heavy-tailed distributions of price changes. Then we calibrate Markov regime-switching (MRS) models with heavy-tailed components and show that they adequately address the aforementioned characteristics. Contrary to the common belief that electricity price models ‘should be built on log-prices’, we find evidence that modeling the prices themselves is more beneficial and methodologically sound, at least in case of MRS models.     

The traveling purchaser problem with stochastic prices: Exact and approximate algorithms

The paper formulates an extension of the traveling purchaser problem where multiple types of commodities are sold at spatially distributed locations with stochastic prices (each following a known probability distribution). A purchaser’s goal is to find the optimal routing and purchasing strategies that minimize the expected total travel and purchasing costs needed to purchase one unit of each commodity. The purchaser reveals the actual commodity price at a seller upon arrival, and then either purchases the commodity at the offered price, or rejects the price and visits a next seller. In this paper, we propose an exact solution algorithm based on dynamic programming, an iterative approximate algorithm that yields bounds for the minimum total expected cost, and a greedy heuristic for fast solutions to large-scale applications. We analyze the characteristics of the problem and test the computational performance of the proposed algorithms. The numerical results show that the approximate and heuristic algorithms yield near-optimum strategies and very good estimates of the minimum total cost.