Dynamic optimization can apply powerful optimizations to hot execution paths that span traditional boundaries such as branches and calls, including calls to dynamic libraries. Because of this opportunity, it has gained academic and industrial attention. In this paper, we examine dynamic optimization in an overhead-free environment to ascertain its optimization potential. Specifically, we explor...

parametric design optimization of an automotive body crashworthiness improvement is presented. the thicknesses of parts are employed as design variables for optimization whose objective is to increase the maximum deceleration value of the vehicle center of gravity during an impact. using the taguchi method, this study analyzes the optimum conditions for design objectives and the impact factors ...

Pareto optimization combines independent objectives by computing the Pareto front of the search space, yielding a set of optima where none scores better on all objectives than any other. Recently, it was shown that Pareto optimization seamlessly integrates with algebraic dynamic programming: when scoring schemes A and B can correctly evaluate the search space via dynamic programming, then so ca...

In this paper, we reconsider the analytical results on the existence of cyclical fluctuations in continuous time dynamic optimization models with two state variables and their applications to dynamic economic theory. In the first part of the paper, we survey the useful analytical results which were obtained by Dockner and Feichtinger(1991), Liu(1994) and Asada and Yoshida(2003) on the general t...

In this paper, we have proposed a study on controllability and optimal harvestingof a prey predator model and mathematical non linear formation of the equation equilibriumpoint of Routh harvest stability analysis. The problem of determining the optimal harvestpolicy is solved by invoking Pontryagin0s maximum principle dynamic optimization of theharvest policy is studied by taking the combined h...

A novel optimization algorithm, called accelerated particle swarm optimization (APSO), is proposed to be used for dynamic spectrum sensing in cognitive radio networks. While modified swarm-based optimization algorithms focus on slight variations of the standard mathematical formulas, in APSO, the acceleration variable of the particles is also considered in the search space. We show that the pro...

In this paper we present a model of international interest rate arbitrage under conditions of entry and exit costs to and from the domestic capital market. We seek to measure the maximum potential effect of capital controls, such as non-interest paying reserve requirements, on interest rate differentials. We quantify the effect of such taxes using a dynamic optimization model with uncertainty a...