Outputs (11)

Hybridising heuristics within an estimation distribution algorithm for examination timetabling (2014)
Journal Article
Qu, R., Pham, D. N. T., Bai, R., & Kendall, G. (2015). Hybridising heuristics within an estimation distribution algorithm for examination timetabling. Applied Intelligence, 42(4), 679-693. https://doi.org/10.1007/s10489-014-0615-0

This paper presents a hybrid hyper-heuristic approach based on estimation distribution algorithms. The main motivation is to raise the level of generality for search methodologies. The objective of the hyper-heuristic is to produce solutions of accep... Read More about Hybridising heuristics within an estimation distribution algorithm for examination timetabling.

Search with evolutionary ruin and stochastic rebuild: a theoretic framework and a case study on exam timetabling (2014)
Journal Article
Li, J., Bai, R., Shen, Y., & Qu, R. (in press). Search with evolutionary ruin and stochastic rebuild: a theoretic framework and a case study on exam timetabling. European Journal of Operational Research, 242(3), https://doi.org/10.1016/j.ejor.2014.11.002

This paper presents a state transition based formal framework for a new search method, called Evolutionary Ruin and Stochastic Recreate, which tries to learn and adapt to the changing environments during the search process. It improves the performanc... Read More about Search with evolutionary ruin and stochastic rebuild: a theoretic framework and a case study on exam timetabling.

A learning-guided multi-objective evolutionary algorithm for constrained portfolio optimization (2014)
Journal Article
Lwin, K., Qu, R., & Kendall, G. (2014). A learning-guided multi-objective evolutionary algorithm for constrained portfolio optimization. Applied Soft Computing, 24, https://doi.org/10.1016/j.asoc.2014.08.026

Portfolio optimization involves the optimal assignment of limited capital to different available financial assets to achieve a reasonable trade-off between profit and risk objectives. In this paper, we studied the extended Markowitz's mean-variance p... Read More about A learning-guided multi-objective evolutionary algorithm for constrained portfolio optimization.

On minimizing coding operations in network coding based multicast: an evolutionary algorithm (2014)
Journal Article
Xing, H., Qu, R., Bai, L., & Ji, Y. (2014). On minimizing coding operations in network coding based multicast: an evolutionary algorithm. Applied Intelligence, 41(3), https://doi.org/10.1007/s10489-014-0559-4

In telecommunications networks, to enable a valid data transmission based on network coding, any intermediate node within a given network is allowed, if necessary, to perform coding operations. The more coding operations needed, the more coding resou... Read More about On minimizing coding operations in network coding based multicast: an evolutionary algorithm.

A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems (2014)
Journal Article
He, F., & Qu, R. (2014). A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems. Information Sciences, 289, https://doi.org/10.1016/j.ins.2014.08.028

In this paper, we investigate a multi-period portfolio selection problem with a comprehensive set of real-world trading constraints as well as market random uncertainty in terms of asset prices. We formulate the problem into a two-stage stochastic mi... Read More about A two-stage stochastic mixed-integer program modelling and hybrid solution approach to portfolio selection problems.

Workforce scheduling and routing problems: literature survey and computational study (2014)
Journal Article
Castillo-Salazar, J. A., Landa-Silva, D., & Qu, R. (2016). Workforce scheduling and routing problems: literature survey and computational study. Annals of Operations Research, 239(1), 39-67. https://doi.org/10.1007/s10479-014-1687-2

In the context of workforce scheduling, there are many scenarios in which personnel must carry out tasks at different locations hence requiring some form of transportation. Examples of these type of scenarios include nurses visiting patients at home,... Read More about Workforce scheduling and routing problems: literature survey and computational study.

Adaptive selection of heuristics for improving exam timetables (2014)
Journal Article
Burke, E., Qu, R., & Soghier, A. (2014). Adaptive selection of heuristics for improving exam timetables. Annals of Operations Research, 218(1), https://doi.org/10.1007/s10479-012-1140-3

This paper presents a hyper-heuristic approach which hybridises low-level heuristic moves to improve timetables. Exams which cause a soft-constraint violation in the timetable are ordered and rescheduled to produce a better timetable. It is observed... Read More about Adaptive selection of heuristics for improving exam timetables.

A Dynamic Multiarmed Bandit-Gene Expression Programming Hyper-Heuristic for Combinatorial Optimization Problems (2014)
Journal Article
Sabar, N. R., Ayob, M., Kendall, G., & Qu, R. (2015). A Dynamic Multiarmed Bandit-Gene Expression Programming Hyper-Heuristic for Combinatorial Optimization Problems. IEEE Transactions on Cybernetics, 45(2), 217-228. https://doi.org/10.1109/TCYB.2014.2323936

Hyper-heuristics are search methodologies that aim to provide high-quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain. A traditional hyper-heuristic framework... Read More about A Dynamic Multiarmed Bandit-Gene Expression Programming Hyper-Heuristic for Combinatorial Optimization Problems.

The automatic design of hyper-heuristic framework with gene expression programming for combinatorial optimization problems (2014)
Journal Article
Sabar, N., Ayob, M., Kendall, G., & Qu, R. (2014). The automatic design of hyper-heuristic framework with gene expression programming for combinatorial optimization problems. IEEE Transactions on Evolutionary Computation, https://doi.org/10.1109/TEVC.2014.2319051

Hyper-heuristic approaches aim to automate heuristic design in order to solve multiple problems instead of designing tailor-made methodologies for individual problems. Hyper-heuristics accomplish this through a high level heuristic (heuristic selecti... Read More about The automatic design of hyper-heuristic framework with gene expression programming for combinatorial optimization problems.

Network flow models for intraday personnel scheduling problems (2014)
Journal Article
Brucker, P., & Qu, R. (2014). Network flow models for intraday personnel scheduling problems. Annals of Operations Research, 218(1), https://doi.org/10.1007/s10479-012-1234-y

Personnel scheduling problems can be decomposed into two stages. In the first stage for each employee the working days have to be fixed. In the second stage for each day of the planning period an intraday scheduling problem has to be solved. It consi... Read More about Network flow models for intraday personnel scheduling problems.