Evolutionary Algorithms for Dynamic Optimisation Problems: Design, Analysis and Applications
Lead Research Organisation:
University of Leicester
Department Name: Computer Science
Abstract
Evolutionary algorithms (EAs) have been applied to solve many stationary problems. However, real-world problems are usually more complex and dynamic, where the objective function, decision variables, and environmental parameters may change over time. In this project, we will investigate novel EA approaches to address dynamic optimisation problems (DOPs), a challenging but very important research area. The proposed research has three main aspects: (1) designing and evaluating new EAs for DOPs in collaboration with researchers from Honda Research Institute Europe, (2) theoretically analysing EAs for DOPs, and (3) adapting developed EA approaches to solve dynamic telecommunication optimisation problems. In this project, we will first construct standardised, both discrete and continuous, dynamic test environments based on the concept of problem difficulty, scalability, cyclicity and noise of environments, and standardised performance measures for evaluating EAs for DOPs. Based on the standardised dynamic test and evaluation environment, we will then design and evaluate novel EAs and their hybridisation, e.g., Estimation of Distribution Algorithms (EDAs), Genetic Algorithms, Swarm Intelligence and Adaptive Evolutionary Algorithms, for DOPs based on our previous research. A guiding idea here is to improve EA's adaptability to different degrees of environmental change in the genotypic space, be it binary or not. Systematically and adaptively combining dualism-like schemes for significant changes, random immigration-like schemes for medium changes, and general mutation or variation schemes for small changes, is expected to greatly improve EA's performance in different dynamic environments. And memory schemes can be used when the environment involves cyclic changes. In order to better understand the fundamental issues, theoretical analysis of EAs for DOPs will be pursued in this project. We will apply drift analysis and martingale theory as the starting point to analyse the computational time complexity of EAs for DOPs and the dynamic behaviour of EAs for DOPs regarding such properties as tracking error, tracking velocity, and reliability of arriving at optima. Based on the above EA design, experimental evaluation, and formal analysis, we will then develop a generic framework of EAs for DOPs by extracting key techniques/properties of efficient EAs for DOPs and studying the relationship between them and the characteristics of DOPs being solved with respect to the environmental dynamics in the genotypic space. Another key aspect of this project is to apply and adapt developed EAs for general DOPs to solve core dynamic telecommunications problems, e.g., dynamic frequency assignment problems and dynamic call routing problems, in the real world. We will closely collaborate with researchers from British Telecommunications (BT) to extract domain-specific knowledge and model dynamic telecommunication problems using proper mathematical and graph representations. The obtained domain knowledge will be integrated into our EAs for increased efficiency and effectiveness. All algorithms and software developed in this project will be made available publicly to benefit as many users as possible, whether they are from academe or industry.
Publications
Changhe Li
(2008)
Benchmark generator for CEC 2009 competition on dynamic optimization
Cheng H
(2011)
Joint QoS multicast routing and channel assignment in multiradio multichannel wireless mesh networks using intelligent computational methods
in Applied Soft Computing
Cheng H
(2010)
QoS multicast tree construction in IP/DWDM optical internet by bio-inspired algorithms
in Journal of Network and Computer Applications
Cheng H
(2009)
Stability-aware multi-metric clustering in mobile ad hoc networks with group mobility
in Wireless Communications and Mobile Computing
Cheng H
(2010)
Genetic algorithms with immigrants schemes for dynamic multicast problems in mobile ad hoc networks
in Engineering Applications of Artificial Intelligence
Cheng H
(2009)
A multipopulation parallel genetic simulated annealing-based QoS routing and wavelength assignment integration algorithm for multicast in optical networks
in Applied Soft Computing
Cheng H
(2012)
IMMIGRANTS-ENHANCED MULTI-POPULATION GENETIC ALGORITHMS FOR DYNAMIC SHORTEST PATH ROUTING PROBLEMS IN MOBILE AD HOC NETWORKS
in Applied Artificial Intelligence
Dendir S
(2022)
Race, ethnicity and mortality in the United States during the first year of the COVID-19 pandemic: an assessment.
in Discover social science and health
Jat S
(2010)
A hybrid genetic algorithm and tabu search approach for post enrolment course timetabling
in Journal of Scheduling
Li C
(2012)
A self-learning particle swarm optimizer for global optimization problems.
in IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society
Li Changhe
(2011)
Particle swarm optimization in stationary and dynamic environments
Liu L
(2010)
Particle swarm optimization with composite particles in dynamic environments.
in IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society
Liu L
(2012)
Force-imitated particle swarm optimization using the near-neighbor effect for locating multiple optima
in Information Sciences
Mavrovouniotis M
(2010)
A memetic ant colony optimization algorithm for the dynamic travelling salesman problem
in Soft Computing
Mavrovouniotis Michalis
(2013)
Ant colony optimization in stationary and dynamic environments
Neri F
(2010)
Guest editorial: Memetic Computing in the presence of uncertainties
in Memetic Computing
Nguyen T
(2012)
Evolutionary dynamic optimization: A survey of the state of the art
in Swarm and Evolutionary Computation
Peng X
(2010)
Environment identification-based memory scheme for estimation of distribution algorithms in dynamic environments
in Soft Computing
Richter H
(2009)
Learning behavior in abstract memory schemes for dynamic optimization problems
in Soft Computing
Shengxiang Yang
(2008)
Population-Based Incremental Learning With Associative Memory for Dynamic Environments
in IEEE Transactions on Evolutionary Computation
Shengxiang Yang
(2010)
Genetic Algorithms With Immigrants and Memory Schemes for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks
in IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
Shengxiang Yang
(2008)
Hyper-Selection in Dynamic Environments
Tinós R
(2010)
Use of the q-Gaussian mutation in evolutionary algorithms
in Soft Computing
Verón EM
(2022)
Participatory process for marine spatial planning: perception of Mar del Plata's residents on offshore hydrocarbon exploration in the North Argentina Basin (Argentina).
in Journal of coastal conservation
Wang H
(2010)
A particle swarm optimization based memetic algorithm for dynamic optimization problems
in Natural Computing
Wang H
(2012)
A memetic particle swarm optimization algorithm for multimodal optimization problems
in Information Sciences
Wang H
(2009)
Adaptive primal-dual genetic algorithms in dynamic environments.
in IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society
Wang H
(2008)
A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems
in Soft Computing
Wang H
(2012)
A memetic particle swarm optimisation algorithm for dynamic multi-modal optimisation problems
in International Journal of Systems Science
Yang S
(2011)
Genetic Algorithms With Guided and Local Search Strategies for University Course Timetabling
in IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
Yang S
(2008)
Genetic algorithms with memory- and elitism-based immigrants in dynamic environments.
in Evolutionary computation
Yang S
(2012)
Metaheuristics for dynamic combinatorial optimization problems
in IMA Journal of Management Mathematics
Yang S
(2009)
An improved constraint satisfaction adaptive neural network for job-shop scheduling
in Journal of Scheduling
Yang S
(2010)
A Clustering Particle Swarm Optimizer for Locating and Tracking Multiple Optima in Dynamic Environments
in IEEE Transactions on Evolutionary Computation
| Description | There are a number of significant new results that were obtained from this project. First, we have developed a series of benchmark dynamic optimisation problem (DOP) generators. For example, the XOR DOP generator can generate DOPs based on any binary-encoded functions. The Generalized Dynamic Benchmark Generator (GDBG) provides a unified approach to constructing DOPs across the binary space, real space, and combinatorial space. These benchmark DOP generators can systematically construct dynamic environments with tunable features and difficulties and hence facilitate the evaluation of algorithms for DOPs. They are now widely used by researchers in the domain. For example, the GDBG was used to generate benchmark DOPs for the 2009 IEEE Competition on Evolutionary Computation in Dynamic and Uncertain Environments, held within the 2009 IEEE Congress on Evolutionary Computation, and the 2012 IEEE Competition on Evolutionary Computation for Dynamic Optimization Problems, held within the 2012 IEEE World Congress on Computational Intelligence. Second, we have systematically studied different approaches to enhancing conventional evolutionary algorithms (EAs) for solving DOPs, and published two review papers in journals in the domain. Several EAs designed by us, e.g., the clustering particle swarm optimizer (CPSO), published in IEEE Transactions on Evolutionary Computation, 14(6): 959-974, 2010, and its variants, have become the state-of-the-art EAs for solving DOPs and are widely used by other researchers to evaluate their algorithms for DOPs. Third, we have pioneered the theoretical analysis of EAs for DOPs based on the dynamical systems approach (or exact model). We described the standard EA as a discrete dynamical system for DOPs. Based on this dynamical systems model, we defined some properties and classes of DOPs and analysed some well-known DOPs in the dynamic evolutionary optimization area. The analysis of DOPs via the dynamical systems approach allows explaining some behaviours observed in experimental results, and hence is important to understand the results obtained in experiments and to analyse the similarity between DOPs. Fourth, we have developed a series of novel evolutionary algorithms for dynamic optimisation problems in wireless and mobile communication networks, including dynamic shortest path routing problems, dynamic multi-cast routing problems, and dynamic clustering problems in mobile ad hoc networks (MANETs). These problems occur frequently in real-world wireless and mobile communication networks, where the topology of networks may change over time. The work on applying evolutionary algorithms for dynamic multi-cast routing problems and dynamic clustering problems in MANETs is a pioneering work in the domain. Fifth, we have extensively studied Ant Colony Optimisation (ACO) algorithms to solve dynamic travelling salesman problems and dynamic vehicle routing problems with traffic factors under random and cyclic dynamic changes. Here, by considering traffic factors, these problems become more challenging and closer to real-world scenarios. Our experimental results showed that our new ACO algorithms outperform other algorithms in the literature on such problems. In total, the findings of the project have led to over 20 journal publications and over 30 conference publications. |
| Exploitation Route | The work has led to new contacts with Rail Safety and Standards Board (RSSB) and Network Rail in addition to original project partners of Honda and BT. A follow on project on "Evolutionary Computation for Dynamic Optimisation in Network Environments" (EP/K001310/1, 02/2013-02/2017) has been funded by EPSRC. In the new EPSRC project, we are closely cooperating with RSSB and Network Rail to model dynamic optimisation problems (e.g., dynamic timetabling and resource scheduling problems) in real-world railway systems, and develop specialised evolutionary computation methods, based on those evolutionary computation methods developed in this EPSRC project, to solve them.This is an excellent route of knowledge transfer because we will contribute our expertise in evolutionary dynamic optimisation to solve problems in real-world railway systems, which is greatly sought by railway industries. 1. Publications in top journals, major conferences, and edited books in the domains of evolutionary computation in general and evolutionary computation in dynamic environments in particular. 2. Source codes of benchmark and test dynamic optimisation problems and developed evolutionary algorithms to solve these problems. They are made available online, which are widely used by domain researchers. 3. New research and application projects in the domain in cooperation with industries. For example, a new EPSRC project on applying evolutionary algorithms to solve dynamic optimisation problems (e.g., dynamic timetabling and resource scheduling problems) in real-world railway systems in cooperation with railway industries is being conducted. |
| Sectors | Digital/Communication/Information Technologies (including Software),Manufacturing, including Industrial Biotechology,Transport |
| URL | http://www.cs.le.ac.uk/projects/EADOP/ |
| Description | Brunel University PhD Scholarship (for an overseas student) |
| Amount | £90,000 (GBP) |
| Organisation | Brunel University London |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 10/2011 |
| End | 09/2015 |
| Description | Evolutionary Computation for Dynamic Optimisation in Network Environments |
| Amount | £445,069 (GBP) |
| Funding ID | EP/K001310/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 02/2013 |
| End | 02/2017 |
| Description | Evolutionary Computation for Dynamic Optimization and Scheduling Problems |
| Amount | ¥150,000 (CNY) |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2010 |
| End | 12/2011 |
| Description | Improved Evolutionary Algorithms with Primal-Dual Population for Dynamic Variation in Production Systems |
| Amount | HK$120,000 (HKD) |
| Funding ID | G-YH60 |
| Organisation | Hong Kong Polytechnic University |
| Sector | Academic/University |
| Country | Hong Kong |
| Start | 07/2009 |
| End | 06/2010 |
| Description | PhD Scholarship |
| Amount | £50,000 (GBP) |
| Organisation | University of Leicester |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 10/2008 |
| End | 09/2011 |
| Description | Collaboration with Hong Kong Polytechnic University |
| Organisation | Hong Kong Polytechnic University |
| Department | Department of Industrial and Systems Engineering |
| Country | Hong Kong |
| Sector | Academic/University |
| PI Contribution | Through this project, I built up/enhanced the strong research collaboration with Dr W.H. Ip from Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, via several research visits, giving seminars, and co-investigation of a research project. |
| Collaborator Contribution | This collaboration led to several journal papers relevant to the EPSRC project. |
| Impact | 1. H. Wang, S. Yang, W. H. Ip, and D. Wang. A memetic particle swarm optimization algorithm for dynamic multi-modal optimization problems. International Journal of Systems Science, 43(7): 1268-1283, July 2012. 2. H. Wang, S. Yang, W. H. Ip, and D. Wang. A particle swarm optimization based memetic algorithm for dynamic optimization problems. Natural Computing, 9(3): 703-725, September 2010. 3. H. Wang, S. Yang, W. H. Ip, and D. Wang. Adaptive primal-dual genetic algorithms in dynamic environments. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics, 39(6): 1348-1361, December 2009. |
| Start Year | 2007 |
| Description | Collaboration with Northeastern University, China |
| Organisation | Northeastern University (China) |
| Department | Key Laboratory of Integrated Automation of Process Industry |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Through this project, I built up/enhanced the strong research collaboration with Prof. Tianyou Chai, Prof. Dingwei Wang, Prof. Xingwei Wang, and Prof. Min Huang from Key Laboratory of Integrated Automation of Process Industry (Northeastern University), Ministry of Education, China, via several research visits, giving seminars, co-supervising PhD students, and co-investigation of two research projects. |
| Collaborator Contribution | This collaboration led to several journal, book and conference papers relevant to the EPSRC project. |
| Impact | Journal Papers: 1. H. Cheng, S. Yang, and X. Wang. Immigrants enhanced multi-population genetic algorithms for dynamic shortest path routing problems in mobile ad hoc networks. Applied Artificial Intelligence, 26(7): 673-695, August 2012. 2. L. Liu, S. Yang, and D. Wang. Force-imitated particle swarm optimization using the near-neighbor effect for locating multiple optima. Information Sciences, 182(1): 139-155, January 2012. 3. L. Liu, S. Yang, and D. Wang. Particle swarm optimization with composite particles in dynamic environments. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics, 40(6): 1634-1648, December 2010. 4. H. Wang, S. Yang, W. H. Ip, and D. Wang. A particle swarm optimization based memetic algorithm for dynamic optimization problems. Natural Computing, 9(3): 703-725, September 2010. 5. H. Cheng, X. Wang, S. Yang, M. Huang, and J. Cao. QoS multicast tree construction in IP/DWDM optical internet by bio-inspired algorithms. Journal of Network and Computer Applications, 33(4): 512-522, July 2010. 6. S. Yang, D. Wang, T. Chai, and G. Kendall. An improved constraint satisfaction adaptive neural network for job-shop scheduling. Journal of Scheduling, 13(1): 17-38, February 2010. 7. H. Wang, S. Yang, W. H. Ip, and D. Wang. Adaptive primal-dual genetic algorithms in dynamic environments. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics, 39(6): 1348-1361, December 2009. 8. H. Wang, D. Wang, and S. Yang. A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems. Soft Computing, 13(8-9): 763-780, July 2009. 9. H. Cheng, J. Cao, X. Wang, S. K. Das, and S. Yang. Stability-aware multi-metric clustering in mobile ad hoc networks with group mobility. Wireless Communications and Mobile Computing, 9(6): 759-771, June 2009. 10. H. Cheng, X. Wang, S. Yang, and M. Huang. A multipopulation parallel genetic simulated annealing based QoS routing and wavelength assignment integration algorithm for multicast in optical networks. Applied Soft Computing, 9(2): 677-684, March 2009. Book chapters: 11. Y. Yan, S. Yang, D. Wang, and D. Wang. Agent based evolutionary dynamic optimization. In R. Sarker and T. Ray (eds.), Agent Based Evolutionary Search, Chapter 5, pp. 97-116, Springer-Verlag Berlin Heidelberg, 2010. 12. H. Cheng, X. Wang, M. Huang, and S. Yang. A review of personal communications services. In K. Y. Chen and H. K. Lee (Eds.), Mobile Computing Research and Applications, Chapter 8, pp. 149-165, Nova Science Publishers, 3rd Quarter, 2009. Conference papers: 13. L. Liu, D. Wang, and S. Yang. An immune system based genetic algorithm using permutation-based dualism for dynamic traveling salesman problems. EvoWorkshops 2009: Applications of Evolutionary Computing, LNCS 5484, pp. 725-734, 2009. 14. H. Cheng, X. Wang, M. Huang, and S. Yang. A review of personal communications services. Proceedings of the 9th International Conference for Young Computer Scientists, pp. 616-621, 2008. 15. Y. Yan, H. Wang, D. Wang, S. Yang, and D. Z. Wang. A multi-agent based evolutionary algorithm in non-stationary environments. Proceedings of the 2008 IEEE Congress on Evolutionary Computation, pp. 2967-2974, 2008. 16. L. Liu, D. Wang, and S. Yang. Compound particle swarm optimization in dynamic environments. In EvoWorkshops 2008: Applications of Evolutionary Computing, LNCS 4974, pp. 616-625, 2008. |
| Start Year | 2008 |
| Title | C++ source codes of genetic algorithms for solving dynamic multicast problems in mobile ad hoc networks |
| Description | The source codes in C++ are the implementation of several genetic algorithms for solving dynamic multicast problems in mobile ad hoc networks, including the genetic algorithms with immigrants schemes developed in the following paper: H. Cheng and S. Yang. Genetic algorithms with immigrants schemes for dynamic multicast problems in mobile ad hoc networks. Engineering Applications of Artificial Intelligence, 23(5): 806-819, August 2010. Elsevier (DOI: 10.1016/j.engappai.2010.01.021). The source codes are available at the following URLs: http://www.tech.dmu.ac.uk/~syang/Codes/dynamic_multicast_general.zip for the General Dynamics Model http://www.tech.dmu.ac.uk/~syang/Codes/dynamic_multicast_worst.zip for the Worst Dynamics Model. |
| Type Of Technology | Software |
| Year Produced | 2010 |
| Open Source License? | Yes |
| Impact | The source codes have been used by a number of domain researchers to benchmark their optimisation algorithms for solving dynamic multicast problems in mobile ad hoc networks. |
| URL | http://www.tech.dmu.ac.uk/~syang/Codes/dynamic_multicast_general.zip |
| Title | C++ source codes of genetic algorithms for solving dynamic shortest path routing problems in mobile ad hoc networks |
| Description | The source codes in C++ are the implementation of several genetic algorithms for solving dynamic shortest path routing problems in mobile ad hoc networks, including the genetic algorithms with immigrants and memory schemes developed in the following paper: S. Yang, H. Cheng, and F. Wang. Genetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks. IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications and Reviews, 40(1): 52-63, January 2010. IEEE Press (DOI: 10.1109/TSMCC.2009.2023676). |
| Type Of Technology | Software |
| Year Produced | 2010 |
| Open Source License? | Yes |
| Impact | The source codes have been used by a number of domain researchers to benchmark their optimisation algorithms for solving dynamic shortest path routing problems in mobile ad hoc networks. |
| URL | http://www.tech.dmu.ac.uk/~syang/Codes/DSP.tar.gz |
| Title | GNU C++ source codes for memory- and elitism-based immigrants genetic algorithms for dynamic optimisation problems |
| Description | The source codes in GNU C++ are the implementation of several genetic algorithms for solving binary dynamic optimisation problems, including the memory- and elitism-based immigrants genetic algorithms developed in the following paper: S. Yang. Genetic algorithms with memory- and elitism-based immigrants in dynamic environments. Evolutionary Computation, 16(3): 385-416, Fall 2008. The MIT Press (DOI: 10.1162/evco.2008.16.3.385). |
| Type Of Technology | Software |
| Year Produced | 2008 |
| Open Source License? | Yes |
| Impact | The source codes have been widely used by other domain researchers to benchmark their optimisation algorithms for binary dynamic optimisation problems. |
| URL | http://www.tech.dmu.ac.uk/~syang/Codes/GA4DOP.tar.gz |
| Title | GNU C++ source codes for the GDBG generator and PSO algorithms for dynamic optimisation problems |
| Description | The source codes in C++ include the implementation of the generalized dynamic benchmark generator (GDBG) developed in the following papers: [1] C. Li and S. Yang. A generalized approach to construct benchmark problems for dynamic optimization. Proceedings of the 7th International Conference on Simulated Evolution and Learning, LNCS 5361, pp. 391-400, 2008. Springer (DOI: 10.1007/978-3-540-89694-4_40). [2] S. Yang and C. Li. A clustering particle swarm optimizer for locating and tracking multiple optima in dynamic environments. IEEE Transactions on Evolutionary Computation, 14(6): 959-974, December 2010. IEEE Press (DOI: 10.1109/TEVC.2010.2046667). The source codes also include the implementation of several particle swarm optimizers (PSO) for solving continuous DOPs, including the clustering PSO (CPSO) developed in the above paper [2]. |
| Type Of Technology | Software |
| Year Produced | 2011 |
| Open Source License? | Yes |
| Impact | The source codes have been widely used by other domain researchers to construct dynamic test problems based on the GDBG generator. And the CPSO algorithm has been widely used by other domain researchers to compare their optimisation algorithms for solving continuous DOPs. The GDBG generator has been used in the IEEE CEC 2009 Competition on Dynamic Optimization and the IEEE WCCI-2012 Competition on Evolutionary Computation for Dynamic Optimization Problems, for deatils see the following Technical Reports. [1] C. Li, S. Yang, and D. A. Pelta. Benchmark Generator for the IEEE WCCI-2012 Competition on Evolutionary Computation for Dynamic Optimization Problems. Technical Report 2011, Department of Information Systems and Computing, Brunel University, U.K., October 2011. This Technical Report is available from http://www.tech.dmu.ac.uk/~syang/ECiDUE/TR-ECDOP-Competition12.pdf. [2] C. Li, S. Yang, T. T. Nguyen, E. L. Yu, X. Yao, Y. Jin, H.-G. Beyer, and P. N. Suganthan. Benchmark generator for CEC 2009 competition on dynamic optimization. Technical Report 2008, Department of Computer Science, University of Leicester, U.K., October 2008. This Technical Report is available from http://www.tech.dmu.ac.uk/~syang/ECiDUE/TR-CEC09-DBG.pdf. |
| URL | http://www.tech.dmu.ac.uk/~syang/Codes/CPSO.tar.gz |
| Title | GNU C++ source codes for the XOR DOP generator and PBIL algorithms for dynamic optimisation problems |
| Description | The source codes in GNU C++ include the implementation of the XOR Dynamic Optimisation Problem (DOP) Generator developed in the following papers: [1] S. Yang. Non-stationary problem optimization using the primal-dual genetic algorithm. Proceedings of the 2003 IEEE Congress on Evolutionary Computation, Vol. 3, pp. 2246-2253, 2003 (DOI: 10.1109/CEC.2003.1299951). [2] S. Yang and X. Yao. Experimental study on population-based incremental learning algorithms for dynamic optimization problems. Soft Computing, 9(11): 815-834, November 2005 (DOI: 10.1007/s00500-004-0422-3). [3] S. Yang and X. Yao. Population-based incremental learning with associative memory for dynamic environments. IEEE Transactions on Evolutionary Computation, 12(5): 542-561, October 2008 (DOI: 10.1109/TEVC.2007.913070). The source codes also include the implementation of several population-based incremental learning (PBIL) and genetic algorithms (GAs) for solving binary DOPs, including the PBIL with associative memory developed in the above paper [3]. |
| Type Of Technology | Software |
| Year Produced | 2008 |
| Open Source License? | Yes |
| Impact | The source codes have been widely used by other domain researchers to construct dynamic test problems based on the XOR DOP generator. |
| URL | http://www.tech.dmu.ac.uk/~syang/Codes/PBIL4DOP.tar.gz |
| Description | Seminar talk, University of Portsmouth, UK, 27th November, 2013 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the School of Creative Technologies, University of Portsmouth, UK on 27th November, 2013. The talk sparkled questions and discussions. |
| Year(s) Of Engagement Activity | 2013 |
| Description | Invited Talk at the BTG Workshop 7: Dynamic Optimisation in an Uncertain World: Challenges and State-of-the-Art, held at University of Birmingham, UK, 24 February 2011 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | I gave an invited talk on "Multi-Population Methods with Clustering in Dynamic Environments" at the BTG Workshop 7: Dynamic Optimisation in an Uncertain World: Challenges and State-of-the-Art, held at the University of Birmingham, UK, 24 February 2011. About 20 people from academia and industries attended the workshop. The talk sparkled questions and discussions. |
| Year(s) Of Engagement Activity | 2011 |
| Description | Organised a Half-day Workshop among RSSB's FuTRO project members and colleagues from Brunel University at Brunel University on 10 January 2012. |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | Attendents from both sides (RSSB's FuTRO team and members from Brunel University) gave short presentations at the workshop and discussed in details future cooperation on the topic of Evolutionary Computation for Dynamic Optimisation Problems in Railway Systems via an EPSRC project proposal. After the workshop, a 4-year project proposal on "Evolutionary Computation for Dynamic Optimisation in Network Environments" was submitted to EPSRC jointly between Brunel University, University of Birmingham, RSSB and Network Rail. The proposal was later accepted by EPSRC and the project has started in February 2013. |
| Year(s) Of Engagement Activity | 2012 |
| Description | Presented an invited talk at Rail Safety and Standards Board (RSSB), London on 23rd November 2011. |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | Yes |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | My talk sparked active questions and discussion afterwards. After my talk, RSSB arranged a visit with a group of people (including 2 staff members from Network Rail) to Brunel University (where I worked from July 2010 to June 2012) to participate a half-day workshop with myself and colleagues from Brunel University on 10 January 2012 for potential cooperation on the topic of Dynamic Optimisation Problems in Railway Systems. |
| Year(s) Of Engagement Activity | 2011 |
| Description | Seminar talk, Anhui University, China, 10 August, 2015. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the School of Computer Science and Technology, Anhui University, China on 10 August, 2015. The talk sparkled questions and discussion afterwards. |
| Year(s) Of Engagement Activity | 2015 |
| Description | Seminar talk, Aston University, UK, 20 May, 2016. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the School of Engineering and Applied Science, Aston University, UK, 20 May, 2016. The talk sparkled questions and discussion afterwards. |
| Year(s) Of Engagement Activity | 2016 |
| Description | Seminar talk, Beijing University of Technology, China, 06 April, 2016. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the College of Electronic Information and Control Engineering, Beijing University of Technology, China on 06 April, 2016. The talk sparkled questions and discussions afterwards and helped establish our research cooperation with the College of Electronic Information and Control Engineering, Beijing University of Technology, China. |
| Year(s) Of Engagement Activity | 2016 |
| Description | Seminar talk, Central South University, China, 24 June, 2016. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the School of Information Science and Engineering, Central South University, China, 24 June, 2016. The talk sparkled questions and discussions afterwards and helped establish our research cooperation with the School. |
| Year(s) Of Engagement Activity | 2016 |
| Description | Seminar talk, Dalian University of Technology, China, 23 July, 2014. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the School of Control Science and Engineering, Dalian University of Technology, China, 23 July, 2014. The talk sparkled questions and discussions. |
| Year(s) Of Engagement Activity | 2014 |
| Description | Seminar talk, Hengyang Normal University, China, 31 March, 2016 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the College of Computer Science and Technology, Hengyang Normal University, China, 31 March, 2016, to over 200 students and staff members. The talk sparkled questions and discussions afterwards. |
| Year(s) Of Engagement Activity | 2016 |
| Description | Seminar talk, Jiangnan University, China, 22 July, 2014 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the School of Internet of Things Engineering, Jiangnan University, China, 22 July, 2014. The talk sparkled questions and discussions and led to future research cooperation. |
| Year(s) Of Engagement Activity | 2014 |
| Description | Seminar talk, Liaocheng University, China, 27 June, 2016. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the School of Computer Science, Liaocheng University, China, 27 June, 2016. The talk sparkled questions and discussions afterwards. |
| Year(s) Of Engagement Activity | 2016 |
| Description | Seminar talk, Loughborough University, UK, 4th December, 2013. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the Department of Computer Science, Loughborough University, UK on 4th December, 2013. The talk sparkled questions and discussions. |
| Year(s) Of Engagement Activity | 2013 |
| Description | Seminar talk, Nanjing University of Aeronautics and Astronautics, China, 21 July, 2014. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the College of Science, Nanjing University of Aeronautics and Astronautics, China on 21 July, 2014. The talk sparkled questions and discussions. |
| Year(s) Of Engagement Activity | 2014 |
| Description | Seminar talk, Nanjing University of Information Science and Technology, China, 30th June, 2011. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the College of Math and Physics, Nanjing University of Information Science and Technology, China, 30th June, 2011. The talk sparkled questions and discussions and led to cooperation with the college. |
| Year(s) Of Engagement Activity | 2011 |
| Description | Seminar talk, Northeastern University, China, 16 July, 2009. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the College of Information Science and Engineering, Northeastern University, China on 16 July, 2009. The talk sparkled questions and discussions afterwards. |
| Year(s) Of Engagement Activity | 2009 |
| Description | Seminar talk, Northeastern University, China, 30 December, 2008 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the College of Information Science and Engineering, Northeastern University, China, 30 December, 2008. The talk sparkled questions and discussion afterwards. |
| Year(s) Of Engagement Activity | 2008 |
| Description | Seminar talk, Northeastern University, China, 30 December, 2010. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the College of Information Science and Engineering, Northeastern University, China on 30 December, 2010. The talk sparkled questions and discussions. |
| Year(s) Of Engagement Activity | 2010 |
| Description | Seminar talk, Shanghai University of Finance and Economics, China, 13 August, 2009 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, China on 13 August, 2009. The talk sparked questions and discussion afterwards. |
| Year(s) Of Engagement Activity | 2009 |
| Description | Seminar talk, University of Essex, UK, 15th March, 2012. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the Department of Mathematical Sciences, University of Essex, UK, 15th March, 2012. The talk sparkled questions and discussions. |
| Year(s) Of Engagement Activity | 2012 |
| Description | Seminar talk, University of Exeter, UK, 25th January, 2012. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the College of Engineering, Mathematics and Physical Sciences, University of Exeter, UK on 25th January, 2012. The talk sparkled questions and discussions. |
| Year(s) Of Engagement Activity | 2012 |
| Description | Seminar talk, University of Kent, UK, 15th March, 2010. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the School of Computing, University of Kent, UK, 15th March, 2010. The talk sparkled questions and discussions. |
| Year(s) Of Engagement Activity | 2010 |
| Description | Seminar talk, University of Warwick, UK, 23rd May, 2013 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at Warwick Business School, University of Warwick, UK on 23rd May, 2013. The talk sparkled questions and discussions afterwards. |
| Year(s) Of Engagement Activity | 2013 |
| Description | Seminar talk, Xiangtan University, China, 29th July, 2012. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | I was invited to give a seminar talk at the College of Information Engineering, Xiangtan University, China, 29th July, 2012. The talk sparkled questions and discussions afterwards. |
| Year(s) Of Engagement Activity | 2012 |
| Description | Workshop Talk at the BTG Application Workshop 1: Real World Routing and Scheduling, University of Birmingham, UK, 9th June 2009. |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Schools |
| Results and Impact | I gave an invited talk on "Evolutionary Computation for Dynamic Optimisation Problems" at the BTG Application Workshop 1: Real World Routing and Scheduling, University of Birmingham, UK, 9th June 2009. Over 20 people from academia and industries attended the workshop. The talk sparkled questions and discussions. |
| Year(s) Of Engagement Activity | 2009 |