The minimization of the fuel costs in the train transportation

Author:
,
Year
: 2006
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.
Keyword(s): Trajectory optimization,Measure theory,Iterative dynamic programming,Optimal

control,Constrained optimization,Linear programming
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