Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case

We have developed a stochastic mathematical formulation for designing a network of multi-product supply chains comprising several capacitated production facilities, distribution centres and retailers in markets under uncertainty. This model considers demand-side and supply-side uncertainties simultaneously, which makes it more realistic in comparison to models in the existing literature. In this model, we consider a discrete set as potential locations of distribution centres and retailing outlets and investigate the impact of strategic facility location decisions on the operational inventory and shipment decisions of the supply chain. We use a path-based formulation that helps us to consider supply-side uncertainties that are possible disruptions in manufacturers, distribution centres and their connecting links. The resultant model, which incorporates the cut-set concept in reliability theory and also the robust optimisation concept, is a mixed integer nonlinear problem. To solve the model to attain global optimality, we have created a transformation based on the piecewise linearisation method. Finally, we illustrate the model outputs and discuss the results through several numerical examples, including a real-life case study from the agri-food industry.     

On the use of fuzzy inference techniques in assessment models: part II: industrial applications

In this paper, we study the applicability of the monotone output property and the output resolution property in fuzzy assessment models to two industrial Failure Mode and Effect Analysis (FMEA) problems. First, the effectiveness of the monotone output property in a single-input fuzzy assessment model is demonstrated with a proposed fuzzy occurrence model. Then, the usefulness of the two properties to a multi-input fuzzy assessment model, i.e., the Bowles fuzzy Risk Priority Number (RPN) model, is assessed. The experimental results indicate that both the fuzzy occurrence model and Bowles fuzzy RPN model are able to fulfill the monotone output property, with the derived conditions (in Part I) satisfied. In addition, the proposed rule refinement technique is able to improve the output resolution property of the Bowles fuzzy RPN model.     

沪深股市风险特征分析

本文运用ARMA-GARCH-M计量经济学模型,以及国际上通行的风险评价指标VAR,通过计算沪深两市的VAR值,比较两市的整体投资风险,以及各自的风险特点,并对模型的有效性进行了Kupiec检验,为投资者控制市场风险提供参考.     

Comonotonic bounds on the survival probabilities in the Lee–Carter model for mortality projection

In the Lee–Carter framework, future survival probabilities are random variables with an intricate distribution function. In large homogeneous portfolios of life annuities, value-at-risk or conditional tail expectation of the total yearly payout of the company are approximately equal to the corresponding quantities involving random survival probabilities. This paper aims to derive some bounds in the increasing convex (or stop-loss) sense on these random survival probabilities. These bounds are obtained with the help of comonotonic upper and lower bounds on sums of correlated random variables.     

带干扰的复合广义齐次Poisson过程的多险种破产概率

将复合广义齐次poisson过程的多险种风险模型推广到带干扰的一种新模型,运用鞅方法破产概率满足的Lundberg不等式和一般公式.     

人寿保险中的投资组合问题

本文考虑与寿险债务匹配的投资组合的一般结构,这种结构中包含了均值-方差有效组合.本文还给出了这种结构中的资产组合的选择和匹配方法以及最优投资组合,并且可以用来确定债务的均值.     

A dynamic stochastic programming model for international portfolio management

We develop a multi-stage stochastic programming model for international portfolio management in a dynamic setting. We model uncertainty in asset prices and exchange rates in terms of scenario trees that reflect the empirical distributions implied by market data. The model takes a holistic view of the problem. It considers portfolio rebalancing decisions over multiple periods in accordance with the contingencies of the scenario tree. The solution jointly determines capital allocations to international markets, the selection of assets within each market, and appropriate currency hedging levels. We investigate the performance of alternative hedging strategies through extensive numerical tests with real market data. We show that appropriate selection of currency forward contracts materially reduces risk in international portfolios. We further find that multi-stage models consistently outperform single-stage models. Our results demonstrate that the stochastic programming framework provides a flexible and effective decision support tool for international portfolio management.     

Portfolio selection with a new definition of risk

In the field of portfolio selection, variance, semivariance and probability of an adverse outcome are three best-known mathematical definitions of risk. Lots of models were built to minimize risk based on these definitions. This paper gives a new definition of risk for portfolio selection and proposes a new type of model based on this definition. In addition, a hybrid intelligent algorithm is employed to solve the optimization problem in general cases. One numerical example is also presented for the sake of illustration.     

A proposed model for co-optimization of energy and reserve in competitive electricity markets

Operating reserve assessment has become increasingly important in the new utility environment in which ancillary services have been assigned a value. This paper presents a procedure for compulsory provision of spinning reserve using a risk-constrained cost-based mechanism. In this mechanism, the electrical energy and spinning reserve are dealt with simultaneously because the provision of reserve cannot be decoupled from the provision of energy. Generators are paid the opportunity cost associated with their reduced energy because compulsion is financially unattractive among them. The transmission system reliability is considered in a simplified manner when computing composite system risk. In the proposed structure, the Independent System Operator (ISO) is responsible for reliability management and is thus responsible for providing sufficient reserve on behalf of the users of the system. The method is applied to the Roy Billinton Test System (RBTS). The General Algebraic Modeling System (GAMS Rev. 140) is used to solve the mixed integer nonlinear co-optimization problems.