Applications of machine learning methods in port operations–A systematic literature review
Ports are pivotal nodes in supply chain and transportation networks, in which most of the
existing data remain underutilized. Machine learning methods are versatile tools to utilize …
existing data remain underutilized. Machine learning methods are versatile tools to utilize …
[HTML][HTML] A systematic literature review for the tourist trip design problem: Extensions, solution techniques and future research lines
J Ruiz-Meza, JR Montoya-Torres - Operations Research Perspectives, 2022 - Elsevier
The tourism sector represents an opportunity for economic growth in countries with tourism
potential. However, new trends in global tourism require efficiency in tourism supply chain …
potential. However, new trends in global tourism require efficiency in tourism supply chain …
How to maximize clicks for display advertisement in digital marketing? A reinforcement learning approach
One of the core challenges in digital marketing is that the business conditions continuously
change, which impacts the reception of campaigns. A winning campaign strategy can …
change, which impacts the reception of campaigns. A winning campaign strategy can …
[HTML][HTML] Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach
Portfolio optimization concerns with periodically allocating the limited funds to invest in a
variety of potential assets in order to satisfy investors' appetites for risk and return goals …
variety of potential assets in order to satisfy investors' appetites for risk and return goals …
A deep reinforcement learning based hyper-heuristic for modular production control
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly
configurable products require an adaptive and robust control approach to maintain …
configurable products require an adaptive and robust control approach to maintain …
[HTML][HTML] Hyper-heuristics: A survey and taxonomy
Hyper-heuristics are search techniques for selecting, generating, and sequencing (meta)-
heuristics to solve challenging optimization problems. They differ from traditional (meta) …
heuristics to solve challenging optimization problems. They differ from traditional (meta) …
[HTML][HTML] A deep reinforcement learning hyper-heuristic with feature fusion for online packing problems
In recent years, deep reinforcement learning has shown great potential in solving computer
games with sequential decision-making scenarios. Hyper-heuristic is a generic search …
games with sequential decision-making scenarios. Hyper-heuristic is a generic search …
Reinforcement learning-assisted evolutionary algorithm: A survey and research opportunities
Evolutionary algorithms (EA), a class of stochastic search methods based on the principles
of natural evolution, have received widespread acclaim for their exceptional performance in …
of natural evolution, have received widespread acclaim for their exceptional performance in …
[HTML][HTML] The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions
Abstract Container Terminals (CTs) are continuously presented with highly interrelated,
complex, and uncertain planning tasks. The ever-increasing intensity of operations at CTs in …
complex, and uncertain planning tasks. The ever-increasing intensity of operations at CTs in …
A selection hyper-heuristic algorithm with Q-learning mechanism
F Zhao, Y Liu, N Zhu, T Xu - Applied Soft Computing, 2023 - Elsevier
The selection of an algorithm in the real world of the application domain is a challenging
problem as no specific algorithm exists capable of solving all issues to a satisfactory …
problem as no specific algorithm exists capable of solving all issues to a satisfactory …