ECDCOP SIGNED
Evolutionary Computation for Dynamic Constrained Optimization Problems
Total Cost €
0EC-Contrib. €
0Partnership
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0ECDCOP project word cloud
Explore the words cloud of the ECDCOP project. It provides you a very rough idea of what is the project "ECDCOP" about.
Project "ECDCOP" data sheet
The following table provides information about the project.
| Coordinator |
DE MONTFORT UNIVERSITY
Organization address contact info |
| Coordinator Country | United Kingdom [UK] |
| Project website | http://www.tech.dmu.ac.uk/ |
| Total cost | 195˙454 € |
| EC max contribution | 195˙454 € (100%) |
| Programme |
1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility) |
| Code Call | H2020-MSCA-IF-2014 |
| Funding Scheme | MSCA-IF-EF-ST |
| Starting year | 2015 |
| Duration (year-month-day) | from 2015-12-01 to 2017-11-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | DE MONTFORT UNIVERSITY | UK (LEICESTER) | coordinator | 195˙454.00 |
Map
Project objective
Evolutionary computation (EC), as an efficient tool, has been widely applied to solve different kinds of stationary optimization problems. However, many real-world optimization problems are dynamic constrained optimization problems (DCOPs), where the objective function, constraints, decision variables, and environmental parameters may change over time. At present, very few attempts have been made to investigate this kind of optimization problems in the communities of optimization and EC. This project aims to fill this gap. In this project, we will concentrate on the design, analysis, and applications of EC for DCOPs, including the following five main aspects. Firstly, we will design a set of benchmark dynamic constrained optimization test environments which can resemble real-world scenarios. Secondly, we intend to design standardized performance indicators to evaluate EC methods for DCOPs. Thirdly, based on the standardized dynamic test and evaluation environments, we will design some novel and effective EC methods to solve DCOPs. Fourthly, we will present theoretical analysis of EC with different constraint-handling techniques for DCOPs, with the aim of establishing the theoretical foundation of this area. Finally, applying the developed EC methods to deal with DCOPs in rail networks is also one key aspect of this project. This project has great potentials to fundamentally change the way in which DCOPs are treated, both from a real-world point of view and from the point of view of advancing our theoretical understanding. The research results of this project will be of great interest to academia in many fields and of significant benefit to many industries that involve DCOPs.
Publications
| year | authors and title | journal | last update |
|---|---|---|---|
| 2018 |
Shouyong Jiang, Shengxiang Yang, Yong Wang, Xiaobin Liu Scalarizing Functions in Decomposition-based Multiobjective Evolutionary Algorithms published pages: 1-1, ISSN: 1089-778X, DOI: 10.1109/TEVC.2017.2707980 |
IEEE Transactions on Evolutionary Computation | 2019-06-18 |
| 2018 |
Zhi-Zhong Liu, Yong Wang, Shengxiang Yang, Ke Tang An Adaptive Framework to Tune the Coordinate Systems in Nature-Inspired Optimization Algorithms published pages: 1-14, ISSN: 2168-2267, DOI: 10.1109/TCYB.2018.2802912 |
IEEE Transactions on Cybernetics | 2019-06-18 |
| 2018 |
Yong Wang, Hao Liu, Huan Long, Zijun Zhang, Shengxiang Yang Differential Evolution with A New Encoding Mechanism for Optimizing Wind Farm Layout published pages: 1-1, ISSN: 1551-3203, DOI: 10.1109/TII.2017.2743761 |
IEEE Transactions on Industrial Informatics | 2019-06-18 |
| 2017 |
Wenyin Gong, Yong Wang, Zhihua Cai, Shengxiang Yang A Weighted Biobjective Transformation Technique for Locating Multiple Optimal Solutions of Nonlinear Equation Systems published pages: 697-713, ISSN: 1089-778X, DOI: 10.1109/TEVC.2017.2670779 |
IEEE Transactions on Evolutionary Computation 21/5 | 2019-06-18 |
| 2018 |
Yong Wang, Da-Qing Yin, Shengxiang Yang, Guangyong Sun Global and Local Surrogate-Assisted Differential Evolution for Expensive Constrained Optimization Problems With Inequality Constraints published pages: 1-15, ISSN: 2168-2267, DOI: 10.1109/TCYB.2018.2809430 |
IEEE Transactions on Cybernetics | 2019-06-18 |
| 2017 |
Yong Wang, Biao Xu, Guangyong Sun, Shengxiang Yang A Two-Phase Differential Evolution for Uniform Designs in Constrained Experimental Domains published pages: 665-680, ISSN: 1089-778X, DOI: 10.1109/TEVC.2017.2669098 |
IEEE Transactions on Evolutionary Computation 21/5 | 2019-06-18 |
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