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All Outputs (27)

Sequential Rule Mining for Automated Design of Meta-heuristics (2023)
Conference Proceeding
Meng, W., & Qu, R. (2023). Sequential Rule Mining for Automated Design of Meta-heuristics. In GECCO’23 Companion: Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (1727-1735). https://doi.org/10.1145/3583133.3596303

With a recently defined AutoGCOP framework, the design of local search algorithms can be defined as the composition of the basic elementary algorithmic components. These compositions into the best algorithms thus retain useful knowledge of effective... Read More about Sequential Rule Mining for Automated Design of Meta-heuristics.

An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem (2022)
Conference Proceeding
Du, X., Bai, R., Cui, T., Qu, R., & Li, J. (2022). An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem. In 2022 IEEE Congress on Evolutionary Computation (CEC). https://doi.org/10.1109/cec55065.2022.9870414

A competitive traveling salesmen problem is a variant of traveling salesman problem in that multiple agents compete with each other in visiting a number of cities. The agent who is the first one to visit a city will receive a reward. Each agent aims... Read More about An Improved Ant Colony Approach for the Competitive Traveling Salesmen Problem.

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.

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.

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.

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.

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.

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.

A survey on cyber security of CAV (2017)
Conference Proceeding
He, Q., Meng, X., & Qu, R. (2017). A survey on cyber security of CAV.

With the ever fast developments of technologies in science and engineering, it is believed that CAV (connected and autonomous vehicles) will come into our daily life soon. CAV could be used in many different aspects in our lives such as public transp... Read More about A survey on cyber security of CAV.

A dynamic truck dispatching problem in marine container terminal (2016)
Conference Proceeding
Chen, J., Bai, R., Dong, H., Qu, R., & Kendall, G. (2016). A dynamic truck dispatching problem in marine container terminal.

In this paper, a dynamic truck dispatching problem of a marine container terminal is described and discussed. In this problem, a few containers, encoded as work instructions, need to be transferred between yard blocks and vessels by a fleet of trucks... Read More about A dynamic truck dispatching problem in marine container terminal.

A quantum inspired evolutionary algorithm for dynamic multicast routing with network coding (2016)
Conference Proceeding
Xing, H., Xu, L., Qu, R., & Qu, Z. (2016). A quantum inspired evolutionary algorithm for dynamic multicast routing with network coding.

This paper studies and models the multicast routing problem with network coding in dynamic network environment, where computational and bandwidth resources are to be jointly optimized. A quantum inspired evolutionary algorithm (QEA) is developed to a... Read More about A quantum inspired evolutionary algorithm for dynamic multicast routing with network coding.

Hybridising local search with Branch-and-Bound for constrained portfolio selection problems (2016)
Conference Proceeding
He, F., & Qu, R. (2016). Hybridising local search with Branch-and-Bound for constrained portfolio selection problems.

In this paper, we investigate a constrained portfolio selection problem with cardinality constraint, minimum size and position constraints, and non-convex transaction cost. A hybrid method named Local Search Branch-and-Bound (LS-B&B) which integrates... Read More about Hybridising local search with Branch-and-Bound for constrained portfolio selection problems.

Towards an efficient API for optimisation problems data (2016)
Conference Proceeding
Pinheiro, R. L., Landa-Silva, D., Qu, R., Yanaga, E., & Constantino, A. A. (2016). Towards an efficient API for optimisation problems data. In . S. Hammoudi, . L. Maciaszek, . M. M. Missikoff, O. Camp, & . J. Cordeiro (Eds.), Proceedings of the 18th International Conference on Enterprise Information Systems . Volume 2: ICEIS (89-98). https://doi.org/10.5220/0005915800890098

The literature presents many application programming interfaces (APIs) and frameworks that provide state of the art algorithms and techniques for solving optimisation problems. The same cannot be said about APIs and frameworks focused on the problem... Read More about Towards an efficient API for optimisation problems data.

A variable neighbourhood search algorithm with compound neighbourhoods for VRPTW (2016)
Conference Proceeding
Chen, B., Qu, R., Bai, R., & Ishibuchi, H. (2016). A variable neighbourhood search algorithm with compound neighbourhoods for VRPTW.

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)
Conference Proceeding
Jin, Y., Qu, R., & Atkin, J. (2016). Constrained portfolio optimisation: the state-of-the-art Markowitz models.

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.

A compromise based fuzzy goal programming approach with satisfaction function for multi-objective portfolio optimisation (2015)
Conference Proceeding
He, F., Qu, R., & John, R. (2015). A compromise based fuzzy goal programming approach with satisfaction function for multi-objective portfolio optimisation.

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.

A greedy heuristic for workforce scheduling and routing with time-dependent activities constraints (2015)
Conference Proceeding
Castillo-Salazar, J. A., Landa-Silva, D., & Qu, R. (2015). A greedy heuristic for workforce scheduling and routing with time-dependent activities constraints.

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.

Computational study for workforce scheduling and routing problems (2014)
Conference Proceeding
Castillo-Salazar, J. A., Landa-Silva, D., & Qu, R. (2014). Computational study for workforce scheduling and routing problems.

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.