All Outputs (8)

A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices (2019)
Journal Article
Cui, T., Bai, R., Ding, S., Parkes, A. J., Qu, R., He, F., & Li, J. (2020). A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices. Soft Computing, 24, 2809–2831. https://doi.org/10.1007/s00500-019-04517-y

© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Portfolio optimization is one of the most important problems in the finance field. The traditional Markowitz mean-variance model is often unrealistic since it relies on the perfect market... Read More about A hybrid combinatorial approach to a two-stage stochastic portfolio optimization model with uncertain asset prices.

Information Retrieval for Evidence-Based Policy Making Applied to Lifelong Learning (2019)
Presentation / Conference Contribution
Clos, J., Qu, R., & Atkin, J. (2019). Information Retrieval for Evidence-Based Policy Making Applied to Lifelong Learning. In Artificial Intelligence XXXVI (487-493). https://doi.org/10.1007/978-3-030-34885-4_41

© 2019, Springer Nature Switzerland AG. Policy making involves an extensive research phase during which existing policies which are similar to the one under development need to be retrieved and analysed. This phase is time-consuming for the following... Read More about Information Retrieval for Evidence-Based Policy Making Applied to Lifelong Learning.

A Survey of Deep Learning-Based Object Detection (2019)
Journal Article
Jiao, L., Zhang, F., Liu, F., Yang, S., Li, L., Feng, Z., & Qu, R. (2019). A Survey of Deep Learning-Based Object Detection. IEEE Access, 7, 128837-128868. https://doi.org/10.1109/access.2019.2939201

A variable neighborhood search algorithm with reinforcement learning for a real-life periodic vehicle routing problem with time windows and open routes (2019)
Journal Article
Chen, B., Qu, R., Bai, R., & Laesanklang, W. (2020). A variable neighborhood search algorithm with reinforcement learning for a real-life periodic vehicle routing problem with time windows and open routes. RAIRO: Operations Research, 54(5), 1467-1494. https://doi.org/10.1051/ro/2019080

Based on a real-life container transport problem, a model of Open Periodic Vehicle Routing Problem with Time Windows (OPVRPTW) is proposed in this paper. In a wide planning horizon, which is divided into a number of shifts, a fixed number of trucks a... Read More about A variable neighborhood search algorithm with reinforcement learning for a real-life periodic vehicle routing problem with time windows and open routes.

Accelerated genetic algorithm based on search-space decomposition for change detection in remote sensing images (2019)
Journal Article
Mu, C., Li, C., Liu, Y., Qu, R., & Jiao, L. (2019). Accelerated genetic algorithm based on search-space decomposition for change detection in remote sensing images. Applied Soft Computing, 84, Article 105727. https://doi.org/10.1016/j.asoc.2019.105727

Detecting change areas among two or more remote sensing images is a key technique in remote sensing. It usually consists of generating and analyzing a difference image thus to produce a change map. Analyzing the difference image to obtain the change... Read More about Accelerated genetic algorithm based on search-space decomposition for change detection in remote sensing images.

Controlling understaffing with conditional Value-at-Risk constraint for an integrated nurse scheduling problem under patient demand uncertainty (2019)
Journal Article
He, F., Chaussalet, T., & Qu, R. (2019). Controlling understaffing with conditional Value-at-Risk constraint for an integrated nurse scheduling problem under patient demand uncertainty. Operations Research Perspectives, 6, Article 100119. https://doi.org/10.1016/j.orp.2019.100119

Nursing workforce management is a challenging decision-making task in hospitals. The decisions are made across different timescales and levels from strategic long-term staffing budget to mid-term scheduling. These decisions are interconnected and imp... Read More about Controlling understaffing with conditional Value-at-Risk constraint for an integrated nurse scheduling problem under patient demand uncertainty.

Modelling the home health care nurse scheduling problem for patients with long-term conditions in the UK (2019)
Presentation / Conference Contribution
He, F., Chaussalet, T., & Qu, R. (2019). Modelling the home health care nurse scheduling problem for patients with long-term conditions in the UK.

In this work, using a Behavioural Operational Research (BOR) perspective, we develop a model for the Home Health Care Nurse Scheduling Problem (HHCNSP) with application to renal patients taking Peritoneal Dialysis (PD) at their own homes as treatment... Read More about Modelling the home health care nurse scheduling problem for patients with long-term conditions in the UK.

Multi-objective ant colony optimization algorithm based on decomposition for community detection in complex networks (2019)
Journal Article
Mu, C., Zhang, J., Liu, Y., Qu, R., & Huang, T. (2019). Multi-objective ant colony optimization algorithm based on decomposition for community detection in complex networks. Soft Computing, 23, 12683-12709. https://doi.org/10.1007/s00500-019-03820-y

Community detection aims to identify topological structures and discover patterns in complex networks, which presents an important problem of great significance. The problem can be modeled as an NP hard combinatorial optimization problem, to which mu... Read More about Multi-objective ant colony optimization algorithm based on decomposition for community detection in complex networks.