A profit-maximizing supply chain network design model with demand choice flexibility

We present a profit-maximizing supply chain design model in which a company has flexibility in determining which customers to serve. The company may lose a customer to competition if the price it charges is too high. We show the problem formulation and solution algorithm, and discuss computational results.     

单件小批生产系统下模糊优化的动态随机投入产出模型

本文针对单件小批量生产系统 ,建立了模糊优化的动态随机投入产出模型 ,同时给出了该模型的递推解法 ,并用此模型对某单件小批企业在生产计划期的商品量进行了规划     

A slacks-based measure of efficiency in data envelopment analysis

In this paper, we will propose a slacks-based measure (SBM) of efficiency in Data Envelopment Analysis (DEA). This scalar measure deals directly with the input excesses and the output shortfalls of the decision making unit (DMU) concerned. It is units invariant and monotone decreasing with respect to input excess and output shortfall. Furthermore, this measure is determined only by consulting the reference-set of the DMU and is not affected by statistics over the whole data set. The new measure has a close connection with other measures proposed so far, e.g., Charnes–Cooper–Rhodes (CCR), Banker–Charnes–Cooper (BCC) and the Russell measure of efficiency. The dual side of this model can be interpreted as profit maximization, in contrast to the ratio maximization of the CCR model. Numerical experiments show its validity as an efficiency measurement tool and its compatibility with other measures of efficiency.     

备货型商品在三种销售价格下的利润函数（I）

本文考虑的是备货型商品的生产与优化管理。商品的生产过程是随机可控的。需求过程是一个根据销售价格高低来控制的随机过程。本文主要研究是这样一个系统的利润函数。     

Quantile regression for modelling distributions of profit and loss

Quantile regression is applied in two retail credit risk assessment exercises exemplifying the power of the technique to account for the diverse distributions that arise in the financial service industry. The first application is to predict loss given default for secured loans, in particular retail mortgages. This is an asymmetric process since where the security (such as a property) value exceeds the loan balance the banks cannot retain the profit, whereas when the security does not cover the value of the defaulting loan then the bank realises a loss. In the light of this asymmetry it becomes apparent that estimating the low tail of the house value is much more relevant for estimating likely losses than estimates of the average value where in most cases no loss is realised. In our application quantile regression is used to estimate the distribution of property values realised on repossession that is then used to calculate loss given default estimates. An illustration is given for a mortgage portfolio from a European mortgage lender. A second application is to revenue modelling. While credit issuing organisations have access to large databases, they also build models to assess the likely effects of new strategies for which, by definition, there is no existing data. Certain strategies are aimed at increasing the revenue stream or decreasing the risk in specific market segments. Using a simple artificial revenue model, quantile regression is applied to elucidate the details of subsets of accounts, such as the least profitable, as predicted from their covariates. The application uses standard linear and kernel smoothed quantile regression.     

Price-sensitive demand for perishable items - an EOQ model

This paper develops a finite time-horizon deterministic EOQ (Economic Order Quantity) model where the rate of demand decreases quadratically with selling price. Prices at different periods are considered as decision variables. The objective is to find the optimal ordering quantity and optimal sales prices that maximizes the vendor’s total profit. The results are discussed with numerical examples. Sensitivity analysis of the optimal solution with respect to the key parameters of the system is carried out.     

Decomposing profit inefficiency in DEA through the weighted additive model

An issue that has received little attention in the Data Envelopment Analysis literature is the decomposition of profit inefficiency by means of measures that account all sources of technical inefficiency. In this paper we introduce a new way to measure and decompose profit inefficiency through weighted additive models. All our results are derived from a new Fenchel-Mahler inequality using duality theory.     

Stokes integral of economic growth: Calculus and the Solow model

Economic growth depends on capital and labor and two-dimensional calculus has been applied to economic theory. This leads to Riemann and Stokes integrals and to the first and second laws of production and growth. The mathematical structure is the same as in thermodynamics, economic properties may be related to physical terms: capital to energy, production to physical work, GDP per capita to temperature, production function to entropy. This is called econophysics. Production, trade and banking may be compared to motors, heat pumps or refrigerators. The Carnot process of the first law creates two levels in each system: cold and hot in physics; buyer and seller, investor and saver, rich and poor in economics. The efficiency rises with the income difference of rich and poor. The results of econophysics are compared to neoclassical theory.     

Comparative analysis of the machine repair Problem with imperfect coverage and service pressure condition

In this paper we analyze the warm-standby M/M/R machine repair problem with multiple imperfect coverage which involving the service pressure condition. When an operating machine (or warm standby) fails, it may be immediately detected, located, and replaced with a coverage probability c by a standby if one is available. We use a recursive method to develop the steady-state analytic solutions which are used to calculate various system performance measures. The total expected profit function per unit time is derived to determine the joint optimal values at the maximum profit. We first utilize the direct search method to measure the various characteristics of the profit function followed by Quasi-Newton method to search the optimal solutions. Furthermore, the particle swarm optimization (PSO) algorithm is implemented to find the optimal combinations of parameters in the pursuit of maximum profit. Finally, a comparative analysis of the Quasi-Newton method with the PSO algorithm has demonstrated that the PSO algorithm provides a powerful tool to perform the optimization problem.     

The impact of disaster on the strategic interaction between company and government

A company allocates a resource between safety effort and production. The government earns taxes on production. The disaster probability is modeled as a contest between the disaster magnitude and the two players’ safety efforts. The model illustrates that safety efforts are strategic substitutes and inverse U shaped in the disaster magnitude. The company’s safety effort increases, and the government’s safety effort decreases, in taxation. Taxation can ameliorate companies’ free riding on governments’ safety efforts. With sufficiently large production, the government prefers, and the company does not prefer, raising taxation above 0%. For the government, an upper limit usually exists above which taxation cannot be profitably increased. The model shows how both or no players exert safety efforts when the disaster magnitude is small and large respectively, and how they free ride on each other’s safety efforts when the disaster magnitude is intermediate. The company free rides when the unit production cost is low so that the large profits outweigh the negative impact of the disaster. With endogenized taxation determined by the government, the tax rate decreases in the disaster magnitude, the unit production cost, the government’s unit cost of safety effort, and how the company is negatively affected by the disaster. The tax rate increases in the company’s resource and how the government is negatively affected by the disaster. The tax rate is weakly U shaped in the company’s unit safety effort. The model is illustrated with numerical examples and with the oil spill disasters by BP in 2010 and by Exxon Valdez in 1989.