All Outputs (105)

A variable neighbourhood search algorithm with compound neighbourhoods for VRPTW (2016)
Presentation / Conference Contribution
Chen, B., Qu, R., Bai, R., & Ishibuchi, H. A variable neighbourhood search algorithm with compound neighbourhoods for VRPTW. Presented at The 2016 International Conference on Operations Research and Enterprise Systems

The Vehicle Routing Problem with Time Windows (VRPTW) consists of constructing least cost routes from a depot to a set of geographically scattered service points and back to the depot, satisfying service time interval and capacity constraints. A Var... Read More about A variable neighbourhood search algorithm with compound neighbourhoods for VRPTW.

Constrained portfolio optimisation: the state-of-the-art Markowitz models (2016)
Presentation / Conference Contribution
Jin, Y., Qu, R., & Atkin, J. Constrained portfolio optimisation: the state-of-the-art Markowitz models. Presented at The 2016 International Conference on Operations Research and Enterprise Systems

This paper studies the state-of-art constrained portfolio optimisation models, using exact solver to identify the optimal solutions or lower bound for the benchmark instances at the OR-library with extended constraints. The effects of pre-assignment,... Read More about Constrained portfolio optimisation: the state-of-the-art Markowitz models.

Good Laboratory Practice for optimization research (2015)
Journal Article
Kendall, G., Bai, R., Blazewicz, J., De Causmaecker, P., Gendreau, M., John, R., Li, J., McCollum, B., Pesch, E., Qu, R., Sabar, N., Vanden Berghe, G., & Yee, A. (2016). Good Laboratory Practice for optimization research. Journal of the Operational Research Society, 67(4), 676-689. https://doi.org/10.1057/jors.2015.77

Good Laboratory Practice has been a part of non-clinical research for over 40 years yet. Optimization Research, despite having many papers discussing standards being published over the same period of time, has yet to embrace standards that underpin i... Read More about Good Laboratory Practice for optimization research.

A Modified Ant Colony Optimization Algorithm for Network Coding Resource Minimization (2015)
Journal Article
Wang, Z., Xing, H., Li, T., Yang, Y., Qu, R., & Pan, Y. (2016). A Modified Ant Colony Optimization Algorithm for Network Coding Resource Minimization. IEEE Transactions on Evolutionary Computation, 20(3), 325-342. https://doi.org/10.1109/TEVC.2015.2457437

The paper presents a modified ant colony optimization approach for the network coding resource minimization problem. It is featured with several attractive mechanisms specially devised for solving the network coding resource minimization problem: 1)... Read More about A Modified Ant Colony Optimization Algorithm for Network Coding Resource Minimization.

A compromise based fuzzy goal programming approach with satisfaction function for multi-objective portfolio optimisation (2015)
Presentation / Conference Contribution
He, F., Qu, R., & John, R. A compromise based fuzzy goal programming approach with satisfaction function for multi-objective portfolio optimisation. Presented at 29th European Conference on Modelling and Simulation ECMS 2015

In this paper we investigate a multi-objective portfolio selection model with three criteria: risk, return and liquidity for investors. Non-probabilistic uncertainty factors in the market, such as imprecision and vagueness of investors’ preference an... Read More about A compromise based fuzzy goal programming approach with satisfaction function for multi-objective portfolio optimisation.

Price and service competition with maintenance service bundling (2015)
Journal Article
Wang, Y., Sun, L., Qu, R., & Li, G. (2015). Price and service competition with maintenance service bundling. Journal of Systems Science and Systems Engineering, 24(2), https://doi.org/10.1007/s11518-015-5267-z

In many equipment manufacturing industries, firms compete with each other not only on products price, but also on maintenance service. More and more traditional products oriented firms are offering their customers products bundled with maintenance se... Read More about Price and service competition with maintenance service bundling.

A greedy heuristic for workforce scheduling and routing with time-dependent activities constraints (2015)
Presentation / Conference Contribution
Castillo-Salazar, J. A., Landa-Silva, D., & Qu, R. A greedy heuristic for workforce scheduling and routing with time-dependent activities constraints. Presented at International Conference on Operations Research and Enterprise Systems (ICORES 2015)

We present a greedy heuristic (GHI) designed to tackle five time-dependent activities constraints (synchronisation, overlap, minimum difference, maximum difference and minimum-maximum difference) on workforce scheduling and routing problems. These ty... Read More about A greedy heuristic for workforce scheduling and routing with time-dependent activities constraints.

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.

Computational study for workforce scheduling and routing problems (2014)
Presentation / Conference Contribution
Castillo-Salazar, J. A., Landa-Silva, D., & Qu, R. Computational study for workforce scheduling and routing problems. Presented at 3rd International Conference on Operations Research and Enterprise Systems (ICORES 2014)

We present a computational study on 112 instances of the Workforce Scheduling and Routing Problem (WSRP). This problem has applications in many service provider industries where employees visit customers to perform activities. Given their similarity,... Read More about Computational study for workforce scheduling and routing problems.

Hyper-heuristics: a survey of the state of the art (2013)
Journal Article
Burke, E., Gendreau, M., Hyde, M., Kendall, G., Ocha, G., Özcan, E., & Qu, R. (2013). Hyper-heuristics: a survey of the state of the art. Journal of the Operational Research Society, 64, https://doi.org/10.1057/jors.2013.71

Hyper-heuristics comprise a set of approaches that are motivated (at least in part) by the goal of automating the design of heuristic methods to solve hard computational search problems. An underlying strategic research challenge is to develop more g... Read More about Hyper-heuristics: a survey of the state of the art.

Grammatical evolution hyper-heuristic for combinatorial optimization problems (2013)
Journal Article
Sabar, N., Ayob, M., Kendall, G., & Qu, R. (2013). Grammatical evolution hyper-heuristic for combinatorial optimization problems. IEEE Transactions on Evolutionary Computation, 17(6), https://doi.org/10.1109/TEVC.2013.2281527

Designing generic problem solvers that perform well across a diverse set of problems is a challenging task. In this work, we propose a hyper-heuristic framework to automatically generate an effective and generic solution method by utilizing grammatic... Read More about Grammatical evolution hyper-heuristic for combinatorial optimization problems.