改进差分进化算法求解装载率凹费用装箱问题

研究了广泛存在于物流作业中一类新型的装箱问题,主要特征体现在箱子使用费用是关于装载率的凹函数。为求解问题,提出了一种基于分组编码策略的改进差分进化算法,以避免常规实数和整数编码方法存在放大搜索空间的不足。针对分组编码策略,定制化设计了以促进优秀基因传播为导向的新型变异和交叉操作,另外还嵌入了以物品置换为邻域的自适应局部搜索操作以增强局部搜索能力。对以往文献给出算例在不同凹费用函数下进行测试,实验结果显示所提出的算法明显优于BFD启发式算法,并且较遗传算法也有显著性改进。     

Numerical solution of an optimal investment problem with proportional transaction costs

This paper mainly concerns the numerical solution of a nonlinear parabolic double obstacle problem arising in a finite-horizon optimal investment problem with proportional transaction costs. The problem is initially posed in terms of an evolutive HJB equation with gradient constraints and the properties of the utility function allow to obtain the optimal investment solution from a nonlinear problem posed in one spatial variable. The proposed numerical methods mainly consist of a localization procedure to pose the problem on a bounded domain, a characteristics method for time discretization to deal with the large gradients of the solution, a Newton algorithm to solve the nonlinear term in the governing equation and a projected relaxation scheme to cope with the double obstacle (free boundary) feature. Moreover, piecewise linear Lagrange finite elements for spatial discretization are considered. Numerical results illustrate the performance of the set of numerical techniques by recovering all qualitative properties proved in Dai and Yi (2009) [6].     

考虑成本因素的税企博弈模型

本在献[1]的基础上,进一步考虑成本因素在更为一般的条件下建立了新的税企博弈模型,得到国家税务机关最优混合策略及其骗税罚款系数公式,并且指出献[1]的结论是本的一个推论。     

An Exact Procedure for the Resource-Constrained Weighted Earliness–Tardiness Project Scheduling Problem

In this paper we study the resource-constrained project scheduling problem with weighted earliness–tardinesss penalty costs. Project activities are assumed to have a known deterministic due date, a unit earliness as well as a unit tardiness penalty cost and constant renewable resource requirements. The objective is to schedule the activities in order to minimize the total weighted earliness–tardinesss penalty cost of the project subject to the finish–start precedence constraints and the constant renewable resource availability constraints. With these features the problem becomes highly attractive in just-in-time environments.We introduce a depth-first branch-and-bound algorithm which makes use of extra precedence relations to resolve resource conflicts and relies on a fast recursive search algorithm for the unconstrained weighted earliness–tardinesss problem to compute lower bounds. The procedure has been coded in Visual C++, version 4.0 under Windows NT. Both the recursive search algorithm and the branch-and-bound procedure have been validated on a randomly generated problem set.     

A stochastic programming model using an endogenously determined worst case risk measure for dynamic asset allocation

We present a new approach to asset allocation with transaction costs. A multiperiod stochastic linear programming model is developed where the risk is based on the worst case payoff that is endogenously determined by the model that balances expected return and risk. Utilizing portfolio protection and dynamic hedging, an investment portfolio similar to an option-like payoff structure on the initial investment portfolio is characterized. The relative changes in the expected terminal wealth, worst case payoff, and risk aversion, are studied theoretically and illustrated using a numerical example. This model dominates a static mean-variance model when the optimal portfolios are evaluated by the Sharpe ratio. Received: August 15, 1999 / Accepted: October 1, 2000?Published online December 15, 2000     

A Bayesian Decision Theory Approach to Classification Problems

We address the classification problem where an item is declared to be from populationπ_jif certain of its characteristicsvare assumed to be sampled from the distribution with pdf f_j(vθ_j), wherej=1, 2, …, m. We first solve the two population classification problem and then extend the results to the generalmpopulation classification problem. Usually only the form of the pdf's is known. To use the classical classification rule the parameters,θ_j, must be replaced by their estimates. In this paper we allow the parameters of the underlying distributions to be generated from prior distributions. With this added structure, we obtain Bayes rules based on predictive distributions and these are completely determined. Using the first-order expansion of the predictive density, where the coefficients of powers ofn⁻¹remain uniformly bounded innwhen integrated, we obtain an asymptotic bound for the Bayes risk.     

The Minimum Concave Cost Network Flow Problem with fixed numbers of sources and nonlinear arc costs

We prove that the Minimum Concave Cost Network Flow Problem with fixed numbers of sources and nonlinear arc costs can be solved by an algorithm requiring a number of elementary operations and a number of evaluations of the nonlinear cost functions which are both bounded by polynomials inr, n, m, wherer is the number of nodes,n is the number of arcs andm the number of sinks in the network.On leave from Institute of Mathematics, P.O. Box 631, Bo Ho, Hanoi, Vietnam.     

Investors’ preference for a positive tax rate depends on the level of the interest rate

In a financial market with only one stock, Cadenillas and Pliska (Financ Stoch 3:137–165, 1999) showed that sometimes investors can take advantage of a positive tax rate to maximize their portfolio return. Buescu et al. (Math Finance 17:477–485, 2007) generalized this surprising result to a market with one stock and one bank account with zero interest rate. We consider instead a financial market with one stock and one bank account with positive interest rate. As in the papers above, we assume that there are taxes and transaction costs in the financial market. We succeed in solving the problem of an investor who wants to maximize the long-run growth rate of his investment, even though the positivity of the interest rate increases the dimensionality of the problem and the difficulty of the computations. We characterize how the investors’ preference for a positive tax rate depends on the interest rate level: investors prefer a positive tax rate when the level of the interest rate is low, and the opposite occurs when the level of the interest rate is high. Most of the contributions of C. Buescu were made during his doctoral studies at the University of Alberta. The research of C. Buescu and A. Cadenillas was supported by the Social Sciences and Humanities Research Council of Canada grants 410-2003-1401 and 410-2006-1069. We are grateful to Stanley R. Pliska for comments and suggestions to a previous version of the paper, and to the associate editor and referees for constructive remarks. Existing errors are our sole responsibility.     

An improved branch and bound algorithm for minimum concave cost network flow problems

This paper formulates the minimum concave cost network flow (MCCNF) problem as a mixed integer program and solves this program using a new branch and bound algorithm. The algorithm combines Driebeek's up and down penalties with a new technique referred to as the simple bound improvement (SBI) procedure. An efficient numerical method for the SBI procedure is described and computational results are presented which show that the SBI procedure reduces both the in-core storage and the CPU time required to solve the MCCNF problem. In fact, for problems with over 200 binary decision variables, the SBI procedure reduced the in-core storage by more than one-third and the CPU time by more than 40 percent.     

A general unconstrained model for transfer pricing in multinational supply chains

Multinational supply chains operate in more than one country or tax jurisdiction and face decision problems concerned with trade flows of resources, products and services, transfer prices, and allocation of transport costs between their divisions. These decisions must consider, for the sake of optimality, corporate and governmental parameters such as the payment of dividends and royalties, ownership of and control over subsidiaries, income taxes differentials, duties and quotas, etc. In this paper, we generalize and extend the Theory of the Multinational Firm to the case of multinational supply chains. We propose a model that is more general and comprehensive than the previous ones proposed in the literature. To be more specific, our model integrates many of the previous research factors and includes new ones, such as transport costs and duty drawbacks, which are critical for supply chains that operate under international trade regulations. Under the maximization of the repatriated earnings objective, we study the optimality conditions of the corporate decision variables to derive managerial guidelines and to determine how decisions regarding trade quantities, transfer prices, and transport cost allocations affect the amount of taxes to be paid to host governments as well as the total after tax repatriated earnings of the corporation.