The minimization of the fuel costs in the train transportation
سال
: 2006
چکیده: This paper presenting case studies in modern large scale constrained optimization,
the purpose of which is to illustrate how recent advances in algorithms and modelling
languages have made it easy to solve difficult optimization problems using of software.
In this paper we use measure theory technique and iterative dynamic programming
algorithm for solving of a trajectory optimization problem: how to drive a train so as
to minimize fuel costs. In the first method, we optimal control problem to using of
atomic measures change this one to an infinite dimensional linear programming problem
and then we approximate the latter one to a finite dimensional linear programming
problem, then by the optimal solution of the final problem we obtain sub-optimal controls
and then by these controls we obtain the approximate solution of the original
problem. In the second method, we will using dynamic programming as iteration for
solving optimal control problem.
the purpose of which is to illustrate how recent advances in algorithms and modelling
languages have made it easy to solve difficult optimization problems using of software.
In this paper we use measure theory technique and iterative dynamic programming
algorithm for solving of a trajectory optimization problem: how to drive a train so as
to minimize fuel costs. In the first method, we optimal control problem to using of
atomic measures change this one to an infinite dimensional linear programming problem
and then we approximate the latter one to a finite dimensional linear programming
problem, then by the optimal solution of the final problem we obtain sub-optimal controls
and then by these controls we obtain the approximate solution of the original
problem. In the second method, we will using dynamic programming as iteration for
solving optimal control problem.
کلیدواژه(گان): Trajectory optimization,Measure theory,Iterative dynamic programming,Optimal
control,Constrained optimization,Linear programming
کالکشن
:
-
آمار بازدید
The minimization of the fuel costs in the train transportation
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contributor author | سهراب عفتی | en |
contributor author | Sohrab Effati | fa |
date accessioned | 2020-06-06T13:50:46Z | |
date available | 2020-06-06T13:50:46Z | |
date issued | 2006 | |
identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/3371603 | |
description abstract | This paper presenting case studies in modern large scale constrained optimization, the purpose of which is to illustrate how recent advances in algorithms and modelling languages have made it easy to solve difficult optimization problems using of software. In this paper we use measure theory technique and iterative dynamic programming algorithm for solving of a trajectory optimization problem: how to drive a train so as to minimize fuel costs. In the first method, we optimal control problem to using of atomic measures change this one to an infinite dimensional linear programming problem and then we approximate the latter one to a finite dimensional linear programming problem, then by the optimal solution of the final problem we obtain sub-optimal controls and then by these controls we obtain the approximate solution of the original problem. In the second method, we will using dynamic programming as iteration for solving optimal control problem. | en |
language | English | |
title | The minimization of the fuel costs in the train transportation | en |
type | Journal Paper | |
contenttype | External Fulltext | |
subject keywords | Trajectory optimization | en |
subject keywords | Measure theory | en |
subject keywords | Iterative dynamic programming | en |
subject keywords | Optimal control | en |
subject keywords | Constrained optimization | en |
subject keywords | Linear programming | en |
journal title | Applied Mathematics and Computation | en |
journal title | Applied Mathematics and Computation | fa |
journal volume | 0 | |
journal issue | 0 | |
identifier link | https://profdoc.um.ac.ir/paper-abstract-1009378.html | |
identifier articleid | 1009378 |