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Solving the minimum toll revenue problem in real transportation networks
, Article Optimization Letters ; 2014 ; ISSN: 18624472 ; Aashtiani, H. Z ; Sharif University of Technology
Abstract
As a means to relieve traffic congestion, toll pricing has recently received significant attention by transportation planners. Inappropriate use of transportation networks is one of the major causes of network congestion. Toll pricing is a method of traffic management in which traffic flow is guided to proper time and path in order to reduce the total delay in the network. This article investigates a method for solving the minimum toll revenue problem in real and large-scale transportation networks. The objective of this problem is to find link tolls that simultaneously cause users to efficiently use the transportation network and to minimize the total toll revenues to be collected. Although...
Two modified hybrid conjugate gradient methods based on a hybrid secant equation
, Article Mathematical Modelling and Analysis ; Volume 18, Issue 1 , 2013 , Pages 32-52 ; 13926292 (ISSN) ; Mahdavi Amiri, N ; Sharif University of Technology
2013
Abstract
Taking advantage of the attractive features of Hestenes-Stiefel and Dai-Yuan conjugate gradient methods, we suggest two globally convergent hybridizations of these methods following Andrei's approach of hybridizing the conjugate gradient parameters convexly and Powell's approach of nonnegative restriction of the conjugate gradient parameters. In our methods, the hybridization parameter is obtained based on a recently proposed hybrid secant equation. Numerical results demonstrating the efficiency of the proposed methods are reported
An Inexact Newton Method for Nonconvex Equality Constrained Optimization
, M.Sc. Thesis Sharif University of Technology ; Mahdavi Amiri, Nezamoddin (Supervisor)Globally Convergent Limited Memory Bundle Method for Larg-Scale Nonsmooth Optimization
, M.Sc. Thesis Sharif University of Technology ; Mahdavi Amiri, Nezamoddin (Supervisor)Solving a Smooth Approximation of the Sparse Recovery Problem Using the Three-Term Conjugate Gradient Algorithms
, M.Sc. Thesis Sharif University of Technology ; Mahdavi Amiri, Nezamoddin (Supervisor)
Abstract
Line search-based methods are known as a category of the most efficient iterative algo- rithms for solving unconstrained optimization problems. Among them, the conjugate gradient method is of particular importance in solving large-scale contemporary world problems due to its simplicity of structure, low memory requirement and strong convergence characteristics. In spite of the desirable numerical behavior of the conjugate gradient method, this method generally lacks the descent property even for uniformly convex objective functions. To overcome this defect, some effective modifications have been presented in the literature. Amidst, the three-term extension attracted the attention of many...