A hybrid genetic algorithm–neural network strategy for simulation optimization

Simulation optimization aims at determining the best values of input parameters, while the analytical objective function and constraints are not explicitly known in terms of design variables and their values only can be estimated by complicated analysis or time-consuming simulation. In this paper, a hybrid genetic algorithm–neural network strategy (GA–NN) is proposed for such kind of optimization problems. The good approximation performance of neural network (NN) and the effective and robust evolutionary searching ability of genetic algorithm (GA) are applied in hybrid sense, where NNs are employed in predicting the objective value, and GA is adopted in searching optimal designs based on the predicted fitness values. Numerical simulation results and comparisons based on a well-known pressure vessel design problem demonstrate the feasibility and effectiveness of the framework, and much better results are achieved than some existed literature results.     

Stylized facts in internal rates of return on stock index and its derivative transactions

Universal features in stock markets and their derivative markets are studied by means of probability distributions in internal rates of return on buy and sell transaction pairs. Unlike the stylized facts in normalized log returns, the probability distributions for such single asset encounters incorporate the time factor by means of the internal rate of return, defined as the continuous compound interest. Resulting stylized facts are shown in the probability distributions derived from the daily series of TOPIX, S & P 500 and FTSE 100 index close values. The application of the above analysis to minute-tick data of NIKKEI 225 and its futures market, respectively, reveals an interesting difference in the behavior of the two probability distributions, in case a threshold on the minimal duration of the long position is imposed. It is therefore suggested that the probability distributions of the internal rates of return could be used for causality mining between the underlying and derivative stock markets. The highly specific discrete spectrum, which results from noise trader strategies as opposed to the smooth distributions observed for fundamentalist strategies in single encounter transactions may be useful in deducing the type of investment strategy from trading revenues of small portfolio investors.     

Generalized Rule Induction Based on Immune Algorithm

A generalized rule induction mechanism, immune algorithm, for knowledge bases is building an inheritance hierarchy of classes based on the content of their knowledge objects. This hierarchy facilitates group-related processing tasks such as answering set queries, discriminating between objects, finding similarities among objects, etc. Building this hierarchy is a difficult task for knowledge engineers. Conceptual induction may be used to automate or assist engineers in the creation of such a classification structure. This paper introduces a new conceptual rule induction method, which addresses the problem of clustering large amounts of structured objects. The conditions under which the method is applicable are discussed.     

Optimal Security Liquidation Algorithms

This paper develops trading strategies for liquidation of a financial security, which maximize the expected return. The problem is formulated as a stochastic programming problem that utilizes the scenario representation of possible returns. Two cases are considered, a case with no constraint on risk and a case when the risk of losses associated with trading strategy is constrained by Conditional Value-at-Risk (CVaR) measure. In the first case, two algorithms are proposed; one is based on linear programming techniques, and the other uses dynamic programming to solve the formulated stochastic program. The third proposed algorithm is obtained by adding the risk constraints to the linear program. The algorithms provide path-dependent strategies, i.e., the fraction of security sold depends upon price sample-path of the security up to the current moment. The performance of the considered approaches is tested using a set of historical sample-paths of prices.     

Simple Explanation of the No-Free-Lunch Theorem and Its Implications

The no-free-lunch theorem of optimization (NFLT) is an impossibility theorem telling us that a general-purpose, universal optimization strategy is impossible. The only way one strategy can outperform another is if it is specialized to the structure of the specific problem under consideration. Since optimization is a central human activity, an appreciation of the NFLT and its consequences is essential. In this paper, we present a framework for conceptualizing optimization that leads to a simple but rigorous explanation of the NFLT and its implications.     

高校提高综合实力与教师之间的博弈

建立了学校与教师之间的主从微分博弈,证明主从双方最优策略的存在唯一性及其性质.并讨论从方初始值变化时,对其最优策略及主方效用的影响程度.给出主从双方最优策略的求解方法.     

多重均衡选择中的风险占优与混合策略

均衡选择理论是博弈理论的重要组成部分.风险占优均衡是人们经济决策或行为的一个主要结果.利用混合策略及其性质和“抵制”的概念,“支持”了海萨尼和泽尔腾用公理定义的风险占优概念,且具体给出了识别风险占优均衡的标准和方法,并把它们推广到对称博弈中去.最后对均衡占优的直觉概念和风险占优相冲突的一些博弈进行了类似的讨论.     

A zero sum differential game in a Hilbert space

We study a zero sum differential game of fixed duration in a separable Hilbert space. We prove a minimax principle and establish the equivalence between the dynamic programming principle and the existence of a saddle point equilibrium. We also prove sufficient conditions for optimality.     

Assessing the emerging biorefinery sector in Canada

The biorefinery is a key concept used in the strategies and visions of many industrial countries. The potential for Canadian biorefineries based on lignocellulosic forest and agricultural residues is examined. The sector is described in terms of research interests, emerging companies, and established corporate interests. It is found that the Canadian biorefining sector currently has an emphasis on specific bioproduct generation, and the process elements required for a true sugar-based process are in the research phase. A Canadian national strategy should focus on increasing forest industry participation, and increasing collaboration with the provinces, particularly in western Canada.     

离散时间投资组合保险策略CPPI及其实证分析

本文重点讨论了在离散时刻对投资组合进行调整的CPPI策略.给出了组合价值的过程表达式,并对其进行风险分析;引入二次期望效用函数,给出了确定CPPI策略中最优乘数的方法;讨论了借贷限制对CPPI策略的影响并将其与买入持有策略进行比较分析。最后,文章对CPPI策略的投资效果进行了实证分析.