A New Chance-Constrained Maximum Capture Location Problem

The paper presents a new model based on the basic Maximum Capture model, MAXCAP. The new Chance-Constrained Maximum Capture model introduces a stochastic threshold constraint, which recognises the fact that a facility can be open only if a minimum level of demand is captured. A metaheuristic based on Max-Min Ant System and Tabu Search procedure is presented to solve the model. This is the first time that the Max-Min Ant system is adapted to solve a location problem. Computational experience and an application to 55-node network are also presented.     

基于广义最大熵的顾客满意度测评研究

本文提出了应用广义最大熵（Generalized Maximum Entropy,简称 GME）的方法对顾客满意度进行测评,该方法能够处理有限的或者不完全数据.采用了一个应用于美国顾客满意指数（ACSI）的简单模型生成仿真数据,比较GME和PLS两种方法的性能.仿真结果表明,与PLS方法相比,GME方法具有更高的拟合精度和较低的预测误差,在样本数据较少时,表现更为明显.     

考虑顾客使用行为的汽车租赁容量分配策略研究

随着物联网技术的发展, 租赁公司通过智能技术可以实时监测顾客的使用行为, 因此可以根据顾客使用行为设计补贴策略以激励顾客在使用过程中保持良好的行为习惯。本文将租赁价格作为顾客行为的函数, 构建随机动态规划模型, 研究了多产品、多周期下汽车租赁公司的容量分配决策和补贴机制。考虑到所构建模型的状态变量维度较高, 因此提出两种近似算法对模型进行求解, 并通过数值仿真验证了模型的相关性质。在考虑顾客行为可以转变的前提下, 得到相关结论:租赁公司以机会成本作为容量分配决策的重要依据;当所需等级汽车缺货时, 由于低等级汽车的机会成本低于高等级汽车的机会成本, 因此满足升级条件时, 租赁公司总是按照等级顺序进行升级;在合理的补贴策略下, 公司的总收益将会随着补贴的增加而增加。     

Uncertainty and Option Value in Land Allocation Problems

In intensity-modulated radiation therapy (IMRT) not only is the shape of the beam controlled, but combinations of open and closed multileaf collimators modulate the intensity as well. In this paper, we offer a mixed integer programming approach which allows optimization over beamlet fluence weights as well as beam and couch angles. Computational strategies, including a constraint and column generator, a specialized set-based branching scheme, a geometric heuristic procedure, and the use of disjunctive cuts, are described. Our algorithmic design thus far has been motivated by clinical cases. Numerical tests on real patient cases reveal that good treatment plans are returned within 30 minutes. The MIP plans consistently provide superior tumor coverage and conformity, as well as dose homogeneity within the tumor region while maintaining a low irradiation to important critical and normal tissues.     

Optimized Crossover-Based Genetic Algorithms for the Maximum Cardinality and Maximum Weight Clique Problems

In Balas and Niehaus (1996), we have developed a heuristic for generating large cliques in an arbitrary graph, by repeatedly taking two cliques and finding a maximum clique in the subgraph induced by the union of their vertex sets, an operation executable in polynomial time through bipartite matching in the complement of the subgraph. Aggarwal, Orlin and Tai (1997) recognized that the latter operation can be embedded into the framework of a genetic algorithm as an optimized crossover operation. Inspired by their approach, we examine variations of each element of the genetic algorithm—selection, population replacement and mutation—and develop a steady-state genetic algorithm that performs better than its competitors on most problems.     

考虑通货膨胀与最长顾客等待时间的变质性物品的库存模型

本文建立了一种考虑通货膨胀与时间价值的变质性物品的库存模型,在模型中允许短缺发生且拖后的需求速率与在缺货期间已经发生的缺货量有关.和已有相关模型的主要区别在于本模型把一个可重复的订货周期内的最大平均利润的净现值作为目标函数,且增加了在缺货期间最长顾客等待时间的限制,以确保库存系统拥有较高的服务水平.然后讨论了模型最优解的存在性与唯一性,并提供了寻求模型整体最优解的算法.最后用实例说明了此模型在实际中的应用.     

On Resource Allocation Problems with Interval-Scale Coefficients

In this paper we discuss the classical problem of the allocation of a single finite resource among many competing activities for the specific case where the coefficients of the objective function form an interval scale. In this case there is no longer a single optimal solution, but rather a set of efficient solutions. We recommend a technique equivalent to parametric objective function analysis to generate the set of efficient solutions to the problem.     

基于优势粗糙集的极大熵权重下高校招生资源配置方法

高校学科资源的合理配置,对专业的发展前景和社会效益起着非常重要的影响.在构建学科建设绩效指标评价体系的基础上,基于优势粗糙集理论的约简知识,提取出比较有益的偏好决策规则,定性地对专业学科建设情况做出判断.利用极大熵准则对各个评价指标进行合理赋权,得到各个对象的多属性评价值.最后将各方案在最优赋权策略下的得分进行集结,将此比例作为专业招生时的资源配置方法,可以为决策者提供比较公平合理的指导建议.     

Monotone Approximations of Minimum and Maximum Functions and Multi-objective Problems

In this paper the problem of accomplishing multiple objectives by a number of agents represented as dynamic systems is considered. Each agent is assumed to have a goal which is to accomplish one or more objectives where each objective is mathematically formulated using an appropriate objective function. Sufficient conditions for accomplishing objectives are derived using particular convergent approximations of minimum and maximum functions depending on the formulation of the goals and objectives. These approximations are differentiable functions and they monotonically converge to the corresponding minimum or maximum function. Finally, an illustrative pursuit-evasion game example with two evaders and two pursuers is provided.     

Shares Allocation Methods for Generalized Game Problems with Joint Constraints

We consider an extension of a noncooperative game problem where players have joint binding constraints. We suggest a shares allocation approach, which replaces the initial problem with a sequence of Nash equilibrium problems together with an upper level set-valued variational inequality as master problem. This transformation maintains the monotonicity properties of the underlying mappings. We also show that the regularization yields a decomposable penalty method, which removes complex functions in constraints within the custom noncooperative game framework and provides the single-valued master problem with strengthened monotonicity of its cost mapping.     

Cautious Non-Linear Optimisation: A New Technique for Allocation Problems

Solutions of linear programming formulations of some problems may be unsatisfactory, because they inherently tend to be extreme, sparse, and ruthless. A method of non-linear optimisation is described which is cautious in the sense that a progressive restraint is imposed on departures from some reference solution. Constraints can be incorporated provided they are regarded as somewhat flexible. Multiple objectives may also be pursued. Large problems (more than 1000 variables) may be handled without difficulty by employing conjugate gradient methods of optimisation. Computing requirements are no greater than for an equivalent LP problem, and execution times to obtain satisfactory approximate solutions may be less.The method has been successfully applied to a large fishery management problem, which is described. It yields stable, realistic solutions, and enables a range of solutions corresponding to different assumptions about the importance of various processes to be generated with confidence.     

Online Surrogate Problem Methodology for Stochastic Discrete Resource Allocation Problems

We consider stochastic discrete optimization problems where the decision variables are nonnegative integers. We propose and analyze an online control scheme which transforms the problem into a surrogate continuous optimization problem and proceeds to solve the latter using standard gradient-based approaches, while simultaneously updating both the actual and surrogate system states. It is shown that the solution of the original problem is recovered as an element of the discrete state neighborhood of the optimal surrogate state. For the special case of separable cost functions, we show that this methodology becomes particularly efficient. Finally, convergence of the proposed algorithm is established under standard technical conditions; numerical results are included in the paper to illustrate the fast convergence of this approach.     

关于广义线形回归参数极大似然估计相合性的若干问题

本文在广义线性回归中响应变量服从指数型分布且有自然联系的情况下, 讨论了 模型参数的极大似然估计的相合性条件有关的若干问题.     

Sufficient Maximum Principle for Stochastic Optimal Control Problems with General Delays

Journal of Optimization Theory and Applications - This paper is to establish a sufficient maximum principle for one kind of stochastic optimal control problem with three types of delays: a discrete...     

Multiplicity Results for Second Order Nonlinear Problems with Maximum and Minimum

A functional differential equation of the type where F: C¹(J) → L₁(J) is a unbounded operator, is considered. Sufficient conditions for the existence of at least two different solutions satisfying boundary conditions min{x(t): t ? J} = α, max{x(t): t ? J} = β are given.