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In this model,the authors established the integro-differential equation for the expected discounted penalty function at ruin in the case of constant force of interest. 就利息力为常数的情形,给出该模型下破产时刻罚金折现期望满足的积分-微分方程。
The Gerber-Shiu discounted penalty function is considered for the risk modelwith a constant dividend barrier U(t) = u + ct-S(t), S(t) = . The intergrodifferential equation is discussed and solved when claim occurrence relates to Erlang(2) process. 研究了有界风险模型U(t)=u+ct-S(t),S(t)=sum from i=1 to N(t)Y_i中的Gerber-Shiu函数,对索赔到达过程为Erlang(2)过程研究了Gerber-Shiu函数满足的微积分方程并进行求解。
By virtue of studying the properties and the application of the expected discounted penalty function at ruin, this dissertation is devoted to achieving three aspects of work as follows:1. In the classical risk model, Hans U. Gerber and Elias S. W. 一.;Hans U
Expected discounted penalty function 罚金折现期望函数
the expected discounted penalty function 折现罚金函数
Gerber-Shiu expected discounted penalty function Gerber-Shiu罚金折现期望函数
Gerber-Shiu discounted penalty function Gerber-Shiu折现罚金函数
The Expected Discounted Penalty Function of Cox Process with Variable Premium 变保费率风险模型的折现罚金函数
EXPECTED DISCOUNTED PENALTY FUNCTION AT RUIN FOR RISK PROCESS PERTURBED BY DIFFUSION UNDER INTEREST FORCE 带有随机干扰和确定投资回报风险模型下的破产时罚金折现期望
The expected discounted penalty function at ruin during the classical risk process with deterministic return on investment 带有确定投资回报的经典风险过程下的破产时罚金折现期望
Discount Penalty Function and Its Asmptotic Formula in Discrete Trinomial Risk Model 离散三项分布风险模型中的贴现罚函数及其渐近解
Discounted Penalty Function 贴现惩罚函数
Finally, this algorithm is applied to some test problems and it has the better results than using the penalty function algorithm. 最后，本算法应用于几个典型例题，并与罚函数法相比较，数值结果表明该算法是可行的，有效的。
In this paper, we try to apply Binary System Particle Swarm Optimization (BSPSO) with death Penalty function to solve 0/1 knapsack problem. 摘要将带有死亡罚函数的二进制粒子群优化算法应用于0/1背包问题。
expected discounted penalty at ruin 破产时刻罚金折现期望
Penalty function method for solving constrained (minimum) optimization problem of a class of better algorithms. 罚函数方法是求解约束（极小）优化问题的一类较好的算法。
Furthermore.The theory about penalty function method of bilevel multiobjective programming is established. 在单层化的基础上，建立了两层多目标规划的罚函数理论。
Firstly, we can convert the constraint LMIP into unconstraint one by using the penalty function. 通过构造一种罚函数化有约束的LMIP为无约束或简单约束的LMIP。
In the Genetic Algorithm, penalty function is often used to deal with constrains. 摘要在遗传算法中，约束的处理一般采用罚函数法。
Combined with exact non-differentiable penalty function, a new chaos genetic optimization algorithm is presented. 并结合精确不可微罚函数求解非线性约束优化问题，提出了求解此类问题的混沌遗传算法。