模糊线性规划的对称曲边岭形模型

用扩张原理，对模糊线性规划中参数为对称等腰岭形的情形建立了相应的模型化公式，并把这类问题转化为非线性规划求解     

Nonsmooth Calculus, Minimality, and Monotonicity of Convexificators

Noncompact convexificators, which provide upper convex and lower concave approximations for a continuous function, are defined. Various calculus rules, including extremality and mean-value properties, are presented. Regularity conditions are given for convexificators to be minimal. A characterization of quasiconvexity of a continuous function is obtained in terms of the quasimonotonicity of convexificators.     

Some Results on Mathematical Programming with Generalized Ratio Invexity

In this paper, a generalized ratio invexity concept has been applied for single objective fractional programming problems. A concept which has been invoked seems to be more general than the one used earlier by Khan and Hanson in such contexts. Further, duality results for fractional programs have also been obtained.     

不确定性结构的弹塑性分析：模型及其解法

本文处理一类重要的工程问题：不确定性结构的弹塑性分析，分析模型包含了一类分片线性的硬化法则，这包含了大范围实际观察所得的材料特性。我们所处理的不确定性是由荷载及材料参数引起的。本文先把问题转化为一个随机非线性规划问题，然后用逼近技术给出一个简单的求解方法。     

Testing optimality for quadratic 0-1 problems

Received June 4, 1996 / Revised version received November 19, 1997 Published online November 24, 1998     

A branch-and-cut method for 0-1 mixed convex programming

We generalize the disjunctive approach of Balas, Ceria, and Cornuéjols [2] and devevlop a branch-and-cut method for solving 0-1 convex programming problems. We show that cuts can be generated by solving a single convex program. We show how to construct regions similar to those of Sherali and Adams [20] and Lovász and Schrijver [12] for the convex case. Finally, we give some preliminary computational results for our method. Received January 16, 1996 / Revised version received April 23, 1999?Published online June 28, 1999     

关于一例数学建模竞赛题假设合理性的研究

对2001年全国大学生数学建模竞赛C题参考答案的假设中的“奖金在年底发放”提出了异议，认为该假设只是使奖金额达到最大，但方案的可操作性很弱，不符合实际情况．给出了新的符合实际的假设一每年1月1日预留当年奖金，奖金可在一年中任何时候发放，并根据新的假设对C题重新建立了数学模型，得到了新的投资方案．     

Designing an optimal connected nature reserve

We consider a landscape divided into elementary cells, each of these cells containing some species to be protected. We search to select a set of cells to form a natural reserve in order to protect all the species present in the landscape. A species is considered protected if it is present in a certain number of cells of the reserve. There is an important spatial constraint concerning the set of selected cells: a species must be able to go from any cell to any cell without leaving the reserve. An integer linear programming model was proposed by Önal and Briers [2] for this reserve selection problem, but the size of the problems which can be handled by this model is limited: several hours of computation are required for solving instances with hundred of cells and hundred of species. Having proposed an improvement of this model which reduces appreciably the computation time, we propose another integer linear programming model, easy to carry out, which allows to obtain, in a few seconds of computation, optimal or near-optimal solutions for instances with hundred of cells and hundred of species. However, the computation time becomes prohibitive for instances with more than 200 cells and 100 species. But, this approach can be particularly useful to solve the problem, in an approximate way, by aggregation of cells as proposed by Önal and Briers [2].     

Analytical models for supplier selection and order quantity allocation

In the literature, decision models and techniques for supplier selection do not often consider inventory management of the items being purchased as part of the analysis. In this article, two mixed integer nonlinear programming models are proposed to select the best set of suppliers and determine the proper allocation of order quantities while minimizing the annual ordering, inventory holding, and purchasing costs under suppliers’ capacity and quality constraints. The first model allows independent order quantities for each supplier while the second model restricts all order quantities to be of equal size, as it would be required in a multi-stage (supply chain) inventory model. Illustrative examples are used to highlight the advantages of the proposed models over a previous model introduced in the literature.     

Aggregate production planning for process industries under oligopolistic competition

We consider a competitive version of the traditional aggregate production planning model with capacity constraints. In the general case, multiple products are produced by a few competing producers (oligopoly) with limited capacities. Production quantities, prices and consequently profits depend on production and allocation decisions of each producer. In addition, there is competition for the raw material whose supplies are limited, and where prices reflect these limitations. Such situations have recently occurred in several process industry settings including petro-refining, petrochemicals, basic chemicals, cement, fertilizers, pharmaceuticals, rubber, paper, food processing and metals. We use a successive “Bertrand–Cournot” framework to address this problem and to determine optimal production quantities, prices and profits at the producers and at the raw material supplier. Our analysis allows a new way to understand and evaluate the marginal value of additional capacity when there is competition for the market and raw materials.