We obtain closed–form expressions for the prices and optimal hedging strategies of American put–options in the presence of an “up–and–out” barrier, both with and without constraints on the short–selling of stock. The constrained case leads to a stochastic optimization problem of mixed optimal stopping/singular control type. This is reduced to a variational inequality which is then solved explic...

in recent years, wavelet packet modulation ofdm (wpm-ofdm) signals have been introduced for radar applications. these signals have important properties such as inherent high range resolution and high resistance of radar system against jamming reception. this paper investigates the problem of designing these family of signals according to the following criteria: constrained maximization of the d...

An inventory model of a volume flexible manufacturing system for a deteriorating item is developed, taking a stock -dependent demand rate. It is assumed that the demand rate remains stock-dependent for an initial period after which a uniform demand rate follows as the stock comes down to a certain level. The unit production cost is taken to be a function of the finite production rate which is t...

stochastic approach to vehicle routing problem: development and theories abstract in this article, a chance constrained (ccp) formulation of the vehicle routing problem (vrp) is proposed. the reality is that once we convert some special form of probabilistic constraint into their equivalent deterministic form then a nonlinear constraint generates. knowing that reliable computer software for lar...

the issue of unit commitment is one of the most important economic plans in power system. in modern and traditional power systems, in addition to being economical of the planning, the issue of security in unit operation is also of great importance. hence power system operation confronts units’ participation and input considering network security constrains. the issue of units’ participation is ...

Classical statistical models can solve the problem of portfolio optimization and can determine the efficient frontier of investment when there are few investable assets and constraints. But these models cannot easily solve optimization problems when we consider real-world constraints. Therefore, data mining techniques such as evolutionary algorithms are important in portfolio optimization. The ...

The purpose of this research is predicting the stock prices using the Particle Swarm Optimization Algorithm and Box-Jenkins method. In this way, the information of 165 corporations is collected from 2001 to 2016. Then, this research considers price to earnings per share and earnings per share as main variables. The relevant regression equation was created using two variables of earnings per sha...

Constrained optimization problems have a wide range of applications in science, economics, and engineering. In this paper, a neural network model is proposed to solve a class of nonsmooth constrained optimization problems with a nonsmooth convex objective function subject to nonlinear inequality and affine equality constraints. It is a one-layer non-penalty recurrent neural network based on the...

this study focuses on the optimization of the plane structure. sequential quadratic programming (sqp) will be utilized, which is one of the most efficient methods for solving nonlinearly constrained optimization problems. a new formulation for the second order sensitivity analysis of the two-dimensional finite element will be developed. all the second order required derivatives will be calculat...

A decentralized solution to the unsplittable flow problem (UFP) in a transport network is considered, where each flow uses only one route from source to sink and the flows cannot be separated into parts in intermediate nodes. The flow costs in each edge depend on the combination of the assigned flows as well as on external random variables. The distributions of the random variables are unknown,...