the markowitz’s optimization problem is considered as a standard quadratic programming problem that has exact mathematical solutions. considering real world limits and conditions, the portfolio optimization problem is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. therefore, the use of meta-heuristic methods such as neural networks and evolutionar...

in this paper, according to high load capacity and rather large workspace characteristics of cable driven robots (cdrs), maximum dynamic load carrying capacity (dlcc) between two given end points in the workspace along with optimal trajectory is obtained. in order to find dlcc of cdrs, joint actuator torque and workspace of the robot constraints concerning to non-negative tension in cables are ...

In this research, the continuous adjoint method is applied to optimize an airfoil in subsonic and transonic flows. An Euler flow solver is used to analyze the inviscid compressible flow over airfoils in each design cycle. Two design problems appearing in aerodynamic shape optimization, namely inverse pressure design and drag minimization were investigated. In the first part, a test case was car...

Traffic jams and suboptimal traffic flows are ubiquitous in modern societies, and they create enormous economic losses each year. Delays at traffic lights alone account for roughly 10 percent of all delays in US traffic. As most traffic light scheduling systems currently in use are static, set up by human experts rather than being adaptive, the interest in machine learning approaches to this pr...

The problem of portfolio optimization which deals with the twin objectives of minimizing risk and maximizing expected portfolio return can turn complex when constraints that model investor preferences and market norms such as bounding, cardinality and class constraints, and short sales are included in it. A complex-constrained portfolio optimization such as this has been beyond the reach of sol...

Here, a quasi-Newton algorithm for constrained multiobjective optimization is proposed. Under suitable assumptions, global convergence of the algorithm is established.

global optimization methods play an important role to solve many real-world problems. flower pollination algorithm (fp) is a new nature-inspired algorithm, based on the characteristics of flowering plants. in this paper, a new hybrid optimization method called hybrid flower pollination algorithm (fppso) is proposed. the method combines the standard flower pollination algorithm (fp) with the par...

The problem of optimal portfolio selection has attracted a great attention in the finance and optimization field. The future stock price should be predicted in an acceptable precision, and a suitable model and criterion for risk and the expected return of the stock portfolio should be proposed in order to solve the optimization problem. In this paper, two new criterions for the risk of stock pr...