MULTI-OBJECTIVE OPTIMIZATION OF TRAIN SPEED PROFILES ON THE AYAT-MEGENAGNA LINE

Abstract

In this paper, a new approach has been developed
for train speed profile optimization, discrete space
based modeling followed by the determination of an
optimal set of riding modes using multi-objective
optimization techniques. The optimization problem
is formulated by making energy and time as the
components of the two element objective vector
function. A point mass model of the operation of
trains is developed by considering all the important
force components acting on the train. The distance
to travel between stations is discretized into 20
equal length elements where a two stage solution
procedure has been applied to get to the final results.
The first stage of the solution procedure is the
application of a Non dominated Sorting Genetic Algorithm
II (NSGA II) based optimization technique
taking vector of riding modes as the decision variable.
Using the developed algorithms for the calculation
of cost functions, a Pareto-optimal set of riding
modes are determined. The second stage of the solution
process smoothes out the results found in the
previous stage without bringing about considerable
change in the values of the cost functions. Various
speed profiles are generated as optimal for the case
of Ayat to Megenagna line of Addis Ababa Light
Rail Transit (AALRT). The speed profiles that are
generated as the fastest can bring about up to 30%
reduction in headway over the plan. Furthermore,
by choosing the slowest trajectories over the fastest
ones, it is possible to save up to 38.18% of energy,
while 23.98% of reduction in riding time can be
achieved by preferring the fastest profiles over the
slowest ones.