نتایج جستجو برای: stock constrained optimization

تعداد نتایج: 467120  

Performance characteristic of an Unmanned Air Vehicle (UAV) is investigated using a newly developed heuristic approach. Almost all flight phases of any air vehicle can be categorized into trim and maneuvering flights. In this paper, a new envelope called trim-ability envelope, is introduced and sketched within the conventional flight envelope for a small UAV. Optimal maneuverability of the inte...

M. Rezaee–Pajand, Y. Kadkhodaye Bahre

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...

In this research, we proposed a new metaheuristic technique for stock portfolio multi-objective optimization employing the combination of Strength Pareto Evolutionary Algorithm (SPEA), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Arbitrage Pricing Theory (APT). To generate the more precise model, ANFIS has implemented to envisage long-term movement values of the Tehran Stock Exchange (TSE)...

El-henawy, M. Abdel-Baset, O. Abdel-Raouf,

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...

Journal: :European Journal of Operational Research 2012
Jun-ya Gotoh Akiko Takeda

In this paper, we derive a portfolio optimization model by minimizing upper and lower bounds of loss probability. These bounds are obtained under a nonparametric assumption of underlying return distribution by modifying the so-called generalization error bounds for the support vector machine, which has been developed in the field of statistical learning. Based on the bounds, two fractional prog...

2010
James C. Boerkoel Edmund H. Durfee Keith Purrington

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Journal: :Applied Mathematics and Computation 2015
Farzane Fallahati Masoud Allame

In this paper, we investigate on the decomposition method that was presented by Yu and et al. [1]. We show a note about it. © 2015 Elsevier Inc. All rights reserved.

Journal: :TELKOMNIKA (Telecommunication Computing Electronics and Control) 2018

Journal: :Engineering Applications of Artificial Intelligence 2011

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