We propose a penalty-function method for constrained molecular dynamics simulation by defining a quadratic penalty function for the constraints. The simulation with such a method can be done by using a conventional, unconstrained solver only with the penalty parameter increased in an appropriate manner as the simulation proceeds. More specifically, we scale the constraints with their force cons...

We shall provide in this paper good deal pricing bounds for contingent claims induced by the shortfall risk with some loss function. Assumptions we impose on loss functions and contingent claims are very mild. We prove that the upper and lower bounds of good deal pricing bounds are expressed by convex risk measures on Orlicz hearts. In addition, we obtain its representation with the minimal pen...

A family of problems for which the solution is a fixed size set is studied, using fitness functions with varying degrees of epistasis. An empirical comparison between a traditional crossover operator with a binary representation and a penalty function, and the representationindependent Random Assorting Recombination Operator (RAR) is performed. RAR is found to perform marginally better in all c...

Abstract: In this paper we consider the Gerber-Shiu penalty function in the compound binomial risk model with time-correlated claims. It is assumed that each main claim will induce a by-claim but the occurrence of the by-claim may be delayed with a certain probability. Formulas for the probability generating function of the penalty function are obtained, together with the expression for the pen...

The tables of the appendix provide additional numerical results. Table 1 summarizes simulation results for Q-SCAD, LS-SCAD, Q-MCP, LS-MCP with sample sizes 50, 100 and 200 for modeling the 0.7 conditional quantile for the heteroscedastic error setting described in Section 4 of the main paper. The MCP approaches, Q-MCP and LS-MCP, are the equivalent of Q-SCAD and LS-SCAD with the SCAD penalty fu...

We introduce penalty-function-based admission control policies to approximately maximize the expected reward rate in a loss network. These control policies are easy to implement and perform well both in the transient period as well as in steady state. A major advantage of the penalty approach is that it avoids solving the associated dynamic program. However, a disadvantage of this approach is t...

In this paper, we extend the compound binomial model to the case where the premium income process, based on a binomial process, is no longer a linear function. First, a mathematically recursive formula is derived for non ruin probability, and then, we examine the expected discounted penalty function, satisfy a defect renewal equation. Third, the asymptotic estimate for the expected discounted p...

Abstract. In this paper the solution of nonlinear programming problems by a Sequential Quadratic Programming (SQP) trust-region algorithm is considered. The aim of the present work is to promote global convergence without the need to use a penalty function. Instead, a new concept of a “filter” is introduced which allows a step to be accepted if it reduces either the objective function or the co...