需求率为斜坡型的一类变质性物品最优库存策略

本文在考虑需求率服从斜坡型分布的情况下,研究了允许缺货且缺货完全回补、变质率服从威布尔分布、补货率为无穷、有限计划期内的库存模型,证明了最优补货策略的存在性,并给出了求解最优补货策略的算法.     

Holding costs under push or pull conditions - The impact of the Anchor Point

Holding costs are traditionally determined from the investment in physical stock during a cycle. An alternative approach instead derives holding costs from Net Present Value (NPV) functions. It is known that applying both frameworks to the same system can lead to different holding cost valuations, but little explanation has been offered. By introducing the Anchor Point in a model, this paper shows, for four different systems, that traditional holding cost models (implicitly) assume pull conditions, while current NPV approaches model push conditions. This explains in part the differences between the methods. It is shown that the Anchor Point concept allows the construction of NPV models under pull conditions, giving results in better correspondence with traditional models. The traditional framework is restricted to pull conditions and important considerations could be easily overlooked, leading to wrong valuations of holding costs. NPV seems superior as such considerations are automatically incorporated. The application to multi-echelon inventory systems provides interesting insights on the roles of echelon stocks and lead-times, and offers potential for future research.     

Generalized Markov Models of Infectious Disease Spread: A Novel Framework for Developing Dynamic Health Policies

We propose a class of mathematical models for the transmission of infectious diseases in large populations. This class of models, which generalizes the existing discrete-time Markov chain models of infectious diseases, is compatible with efficient dynamic optimization techniques to assist real-time selection and modification of public health interventions in response to evolving epidemiological situations and changing availability of information and medical resources. While retaining the strength of existing classes of mathematical models in their ability to represent the within-host natural history of disease and between-host transmission dynamics, the proposed models possess two advantages over previous models: (1) these models can be used to generate optimal dynamic health policies for controlling spreads of infectious diseases, and (2) these models are able to approximate the spread of the disease in relatively large populations with a limited state space size and computation time.     

考虑事故风险损失的爆炸物品经济订货批量模型研究

爆炸物品在储存过程中存在发生爆炸事故,从而给人类和环境带来伤害的可能,因此在对爆炸物品进行采购决策时必需考虑由此带来的风险损失.在给出爆炸物品事故风险损失度量方法的基础上,建立了爆炸物品的经济订货批量模型,证明了模型存在唯一最优解,并给出了模型的求解步骤,为相关企业合理制定采购决策提供了理论依据.数字算例分析了事故概率、赔偿标准、单位库存费、单次采购费对最优批量的影响,比较了考虑事故风险损失与否时的最优批量,结果表明,当事故概率或赔偿标准较高时,两者对应的最优批量差异明显.这也说明,当事故概率或赔偿标准达到一定程度时,考虑事故风险损失是十分必要的.     

技术不确定环境下新产品策略的设计应用

技术的动态发展和企业间的竞争对企业新产品策略有很大影响,直接决定新产品的引进周期。本文在产业技术动态变化的随机环境下构建随机动态规划模型,关注产业技术进步、投资成本和产品市场竞争等影响因素,探讨企业进行新产品引进的周期选择,对新产品引进的周期和质量决策进行方法设计和应用举例。利用随机动态规划模型得出新产品引进的最优时间周期,用算例分析技术进步和产品研发成本对企业引进周期策略的影响,采取策略迭代的方法进行求解,发现技术进步较快时企业的新产品引进步伐也较快,研发成本的提高使企业的新产品引入步伐降低。     

基于存货质押的库存管理研究

针对基于存货质押的库存管理问题进行分析并构建模型,从还贷和不还贷两个角度,研究模型的最佳订货批量和质押量.模型以利润函数为目标函数,利润函数包括了销售额、缺货损失、剩余品价值、产品成本以及贷款本息和.通过对利润函数进行求解,得出最佳订购批量、存货质押量和最大期望利润,最后根据利润的大小决定是否偿还贷款.     

基于网络均衡的电力市场排污权交易政策研究

本文构建了电力供应链网络均衡模型,网络中包含三级决策主体,分别是:发电厂、电力服务商和用电市场.在分析各级决策者行为的基础上,得到了基于变分不等式的均衡条件,研究了针对发电厂的排污权交易政策设计问题.研究发现:排污交易政策实施后,总排污量不会超过给定的排污权总量;发电厂清洁生产能力的差异对排污权交易政策影响显著.     

退货情形下基于替代率的两产品联合订货决策研究

研究了一类在产品订货模型中考虑客户退货和产品间替代的两产品联合最优订货决策问题.假定客户以一概率退回其所购产品,退货产品经修复后可重新在市场上进行销售,销售期末未售出的商品只能在二级市场上降价处理,且不同产品间存在替代关系,销售商以自身利润最大化为目标确定两产品的订货量,得到其最优订货量及一些性质.研究结果表明:在允许退货的背景下,替代策略的采用将会进一步提高销售商利润.     

Two storage inventory model in a mixed environment

Multi-item inventory models with two storage facility and bulk release pattern are developed with linearly time dependent demand in a finite time horizon under crisp, stochastic and fuzzy-stochastic environments. Here different inventory parameters—holding costs, ordering costs, purchase costs, etc.—are assumed as probabilistic or fuzzy in nature. In particular cases stochastic and crisp models are derived. Models are formulated as profit maximization principle and three different approaches are proposed for solution. In the first approach, fuzzy extension principle is used to find membership function of the objective function and then it’s Graded Mean Integration Value (GMIV) for different optimistic levels are taken as equivalent stochastic objectives. Then the stochastic model is transformed to a constraint multi-objective programming problem using Stochastic Non-linear Programming (SNLP) technique. The multi-objective problems are transferred to single objective problems using Interactive Fuzzy Satisfising (IFS) technique. Finally, a Region Reducing Genetic Algorithm (RRGA) based on entropy has been developed and implemented to solve the single objective problems. In the second approach, the above GMIV (which is stochastic in nature) is optimized with some degree of probability and using SNLP technique model is transferred to an equivalent single objective crisp problem and solved using RRGA. In the third approach, objective function is optimized with some degree of possibility/necessity and following this approach model is transformed to an equivalent constrained stochastic programming problem. Then it is transformed to an equivalent single objective crisp problem using SNLP technique and solved via RRGA. The models are illustrated with some numerical examples and some sensitivity analyses have been presented.     

OPTIMAL IMPULSIVE CONTROL IN COMPETITIVE SYSTEM

In this paper,the impulsive exploitation of two species periodic competitive system is considered.First,we show that this type of system with impulsive har- vesting has a unique positive periodic solution,which is globally asymptotically stable.Further,by choosing the maximum total revenues as the management objective,we investigate the optimal harvesting policies for periodic competi- tive system with impulsive harvesting.Finally,we obtain the optimal time to harvest and optimal population level.