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A Unified Framework of Graph-based Evolutionary Multitasking Hyper-heuristic (2020)
Journal Article
Hao, X., Qu, R., & Liu, J. (2021). A Unified Framework of Graph-based Evolutionary Multitasking Hyper-heuristic. IEEE Transactions on Evolutionary Computation, 25(1), 35-47. https://doi.org/10.1109/tevc.2020.2991717

In recent research, hyper-heuristics have attracted increasing attention among researchers in various fields. The most appealing feature of hyper-heuristics is that they aim to provide more generalized solutions to optimization problems by searching... Read More about A Unified Framework of Graph-based Evolutionary Multitasking Hyper-heuristic.

The General Combinatorial Optimization Problem: Towards Automated Algorithm Design (2020)
Journal Article
Qu, R., Kendall, G., & Pillay, N. (2020). The General Combinatorial Optimization Problem: Towards Automated Algorithm Design. IEEE Computational Intelligence Magazine, 15(2), 14-23. https://doi.org/10.1109/mci.2020.2976182

This paper defines a new combinatorial optimisation problem, namely General Combinatorial Optimisation Problem (GCOP), whose decision variables are a set of parametric algorithmic components, i.e. algorithm design decisions. The solutions of GCOP, i.... Read More about The General Combinatorial Optimization Problem: Towards Automated Algorithm Design.

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)
Conference Proceeding
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 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)
Conference Proceeding
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.

Hyper-heuristics: theory and applications (2018)
Book
Pillay, N., & Qu, R. (2018). Hyper-heuristics: theory and applications. Cham, Switzerland: Springer Nature. doi:10.1007/978-3-319-96514-7

This introduction to the field of hyper-heuristics presents the required foundations and tools and illustrates some of their applications. The authors organized the 13 chapters into three parts. The first, hyper-heuristic fundamentals and theory, pro... Read More about Hyper-heuristics: theory and applications.

Iteration-related various learning particle swarm optimization for quay crane scheduling problem (2018)
Conference Proceeding
Yu, M., Cong, X. C., Niu, B., & Qu, R. (2018). Iteration-related various learning particle swarm optimization for quay crane scheduling problem. In Bio-inspired computing: theories and applications: 13th International Conference, BIC-TA 2018, Beijing, China, November 2–4, 2018, Proceedings, Part II (201-212). https://doi.org/10.1007/978-981-13-2829-9_19

Quay crane scheduling is critical in reducing operation costs at container terminals. Designing a schedule to handling containers in an efficient order can be difficult. For this problem which is proved NP-hard, heuristic algorithms are effective to... Read More about Iteration-related various learning particle swarm optimization for quay crane scheduling problem.

Modified mixed-dimension chaotic particle swarm optimization for liner route planning with empty container repositioning (2018)
Conference Proceeding
Yu, M., Chen, Z., Chen, L., Qu, R., & Niu, B. (2018). Modified mixed-dimension chaotic particle swarm optimization for liner route planning with empty container repositioning. In Bio-inspired Computing: Theories and Applications (296-307). https://doi.org/10.1007/978-981-13-2829-9_27

Empty container repositioning has become one of the important issues in ocean shipping industry. Researchers often solve these problems using linear programming or simulation. For large-scale problems, heuristic algorithms showed to be preferable due... Read More about Modified mixed-dimension chaotic particle swarm optimization for liner route planning with empty container repositioning.

A hyper-heuristic with two guidance indicators for bi-objective mixed-shift vehicle routing problem with time windows (2018)
Journal Article
Chen, B., Qu, R., Bai, R., & Laesanklang, W. (2018). A hyper-heuristic with two guidance indicators for bi-objective mixed-shift vehicle routing problem with time windows. Applied Intelligence, 48(12), 4937–4959. https://doi.org/10.1007/s10489-018-1250-y

In this paper, a Mixed-Shift Vehicle Routing Problem is proposed based on a real-life container transportation problem. In a long planning horizon of multiple shifts, transport tasks are completed satisfying the time constraints. Due to the different... Read More about A hyper-heuristic with two guidance indicators for bi-objective mixed-shift vehicle routing problem with time windows.

Hybrid multi-objective evolutionary algorithms based on decomposition for wireless sensor network coverage optimization (2018)
Journal Article
Xu, Y., Ding, O., Qu, R., & Li, K. (2018). Hybrid multi-objective evolutionary algorithms based on decomposition for wireless sensor network coverage optimization. Applied Soft Computing, 68, 268-282. https://doi.org/10.1016/j.asoc.2018.03.053

In Wireless Sensor Networks (WSN), maintaining a high coverage and extending the network lifetime are two conflicting crucial issues considered by real world service providers. In this paper, we consider the coverage optimization problem in WSN with t... Read More about Hybrid multi-objective evolutionary algorithms based on decomposition for wireless sensor network coverage optimization.

Variable-depth adaptive large meighbourhood search algorithm for Open Periodic Vehicle Routing Problem with time windows (2017)
Conference Proceeding
Chen, B., Qu, R., & Ishibuchi, H. (2017). Variable-depth adaptive large meighbourhood search algorithm for Open Periodic Vehicle Routing Problem with time windows.

The Open Periodic Vehicle Routing Problem with Time Windows (OPVRPTW) is a practical transportation routing and scheduling problem arising from real-world scenarios. It shares some common features with some classic VRP variants. The problem has a tig... Read More about Variable-depth adaptive large meighbourhood search algorithm for Open Periodic Vehicle Routing Problem with time windows.

Change detection in SAR images based on the salient map guidance and an accelerated genetic algorithm (2017)
Conference Proceeding
Mu, C., Li, C., Liu, Y., Sun, M., Jiao, L., & Qu, R. (2017). Change detection in SAR images based on the salient map guidance and an accelerated genetic algorithm. In 2017 IEEE Congress on Evolutionary Computation (CEC) - Proceedings (1150-1157). https://doi.org/10.1109/CEC.2017.7969436

This paper proposes a change detection algorithm in synthetic aperture radar (SAR) images based on the salient image guidance and an accelerated genetic algorithm (S-aGA). The difference image is first generated by logarithm ratio operator based on t... Read More about Change detection in SAR images based on the salient map guidance and an accelerated genetic algorithm.

Information core optimization using Evolutionary Algorithm with Elite Population in recommender systems (2017)
Conference Proceeding
Mu, C., Cheng, H., Feng, W., Liu, Y., & Qu, R. (2017). Information core optimization using Evolutionary Algorithm with Elite Population in recommender systems.

Recommender system (RS) plays an important role in helping users find the information they are interested in and providing accurate personality recommendation. It has been found that among all the users, there are some user groups called “core users”... Read More about Information core optimization using Evolutionary Algorithm with Elite Population in recommender systems.

A hybrid EDA for load balancing in multicast with network coding (2017)
Journal Article
Xing, H., Li, S., cui, Y., Yan, L., Pan, W., & Qu, R. (2017). A hybrid EDA for load balancing in multicast with network coding. Applied Soft Computing, 59, https://doi.org/10.1016/j.asoc.2017.06.003

Load balancing is one of the most important issues in the practical deployment of multicast with network coding. However, this issue has received little research attention. This paper studies how traffic load of network coding based multicast (NCM) i... Read More about A hybrid EDA for load balancing in multicast with network coding.

An improved MOEA/D algorithm for multi-objective multicast routing with network coding (2017)
Journal Article
Xing, H., Wang, Z., Li, T., Li, H., & Qu, R. (2017). An improved MOEA/D algorithm for multi-objective multicast routing with network coding. Applied Soft Computing, 59, https://doi.org/10.1016/j.asoc.2017.05.033

Network coding enables higher network throughput, more balanced traffic, and securer data transmission. However, complicated mathematical operations incur when packets are combined at intermediate nodes, which, if not operated properly, lead to very... Read More about An improved MOEA/D algorithm for multi-objective multicast routing with network coding.