We seek to determine the optimal amount of the insurer’s investment in all types of assets for a small and closed economy. The goal is to detect the implications and contributions the risk seeker and risk aversion insurer commonly make and the effectiveness in the investment decision. Also, finding the optimum portfolio for each is the main goal of the present study. To this end, we adopted the...

Abstract Paired comparisons are a popular tool for questionnaires in psychological marketing research. The quality of the statistical analysis of the responses heavily depends on the design, i.e. the choice of the alternatives in the comparisons. In this paper we show that the structure of locally optimal designs changes substantially with the parameters in the underlying utility. This fact is ...

This paper investigates the problem of allocation of database fragments to a network, so that the overall communication cost for processing a given set of transactions is minimized. Presented first is a data allocation algorithm with respect to a "simple strategy" to process transactions. Secondly, we present a dynamic data allocation algorithm which is guaranteed to produce a "locally optimal"...

In this paper, we propose a new model for designing integrated forward/reverse logistics based on pricing policy in direct and indirect sales channel. The proposed model includes producers, disposal center, distributers and final customers. We assumed that the location of final customers is fixed. First, a deterministic mixed integer linear programming model is developed for integrated logistic...

We develop in this article the first actor–critic reinforcement learning algorithm with function approximation for a problem of control under multiple inequality constraints. We consider the infinite horizon discounted cost framework in which both the objective and the constraint functions are suitable expected policy-dependent discounted sums of certain sample path functions. We apply the Lagr...

a novel approach to determine optimal sampling locations under parameter uncertainty in a water distribution system (wds) for the purpose of its hydraulic model calibration is presented. the problem is formulated as a multi-objective optimisation problem under calibration parameter uncertainty. the objectives are to maximise the calibrated model accuracy and to minimise the number of sampling d...

We study infinite stochastic games played by two-players over a finite state space, with objectives specified by sets of infinite traces. The games are concurrent (players make moves simultaneously and independently), stochastic (the next state is determined by a probability distribution that depends on the current state and chosen moves of the players) and infinite (proceeds for infinite numbe...

Let N( , δ) be the number of samples needed when solving a stochastic program such that the objective function evaluated at the sample optimizer is within of the true optimum with probability 1− δ. Previous results are of the form N( , δ) = O( −2 log δ−1). However, a smooth objective function is often locally quadratic at an interior optimum. For that case we use results on the convergence of t...

Dynamic models give detailed information about the influence of many parameters on the behaviour of the biochemical process of interest. Parameter optimization of dynamic models is used in parameter estimation tasks and in design tasks. A drawback of the popular family of global stochastic optimization methods is the stochastic nature of the convergence of the best value of objective function t...

We present a new method for solving stochastic differential equations based on Galerkin projections and extensions of Wiener’s polynomial chaos. Specifically, we represent the stochastic processes with an optimum trial basis from the Askey family of orthogonal polynomials that reduces the dimensionality of the system and leads to exponential convergence of the error. Several continuous and disc...