Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Machine Learning based Simulation Optimisation for Trailer Management   In many situations, simulation models are developed to handle complex
real-world business optimisation problems. For example, a discrete-event
simulation model is used to simulate the trailer management process in a big
Fast-Moving Consumer Goods company. To address the problem of finding suitable
inputs to this simulator for optimising fleet configuration, we propose a
simulation optimisation approach in this paper. The simulation optimisation
model combines a metaheuristic search (genetic algorithm), with an
approximation model filter (feed-forward neural network) to optimise the
parameter configuration of the simulation model. We introduce an ensure
probability that overrules the rejection of potential solutions by the
approximation model and we demonstrate its effectiveness. In addition, we
evaluate the impact of the parameters of the optimisation model on its
effectiveness and show the parameters such as population size, filter
threshold, and mutation probability can have a significant impact on the
overall optimisation performance. Moreover, we compare the proposed method with
a single global approximation model approach and a random-based approach. The
results show the effectiveness of our method in terms of computation time and
solution quality.

31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
16
The categories of this paper are: stat
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an