Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Online Multimodal Transportation Planning using Deep Reinforcement
  Learning   In this paper we propose a Deep Reinforcement Learning approach to solve a
multimodal transportation planning problem, in which containers must be
assigned to a truck or to trains that will transport them to their destination.
While traditional planning methods work "offline" (i.e., they take decisions
for a batch of containers before the transportation starts), the proposed
approach is "online", in that it can take decisions for individual containers,
while transportation is being executed. Planning transportation online helps to
effectively respond to unforeseen events that may affect the original
transportation plan, thus supporting companies in lowering transportation
costs. We implemented different container selection heuristics within the
proposed Deep Reinforcement Learning algorithm and we evaluated its performance
for each heuristic using data that simulate a realistic scenario, designed on
the basis of a real case study at a logistics company. The experimental results
revealed that the proposed method was able to learn effective patterns of
container assignment. It outperformed tested competitors in terms of total
transportation costs and utilization of train capacity by 20.48% to 55.32% for
the cost and by 7.51% to 20.54% for the capacity. Furthermore, it obtained
results within 2.7% for the cost and 0.72% for the capacity of the optimal
solution generated by an Integer Linear Programming solver in an offline
setting.

11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
2
The categories of this paper are: math
21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat