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ECDCOP SIGNED

Evolutionary Computation for Dynamic Constrained Optimization Problems

Total Cost €

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EC-Contrib. €

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Partnership

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Project "ECDCOP" data sheet

The following table provides information about the project.

Coordinator
DE MONTFORT UNIVERSITY 

Organization address
address: THE GATEWAY
city: LEICESTER
postcode: LE1 9BH
website: www.dmu.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 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.

# participants  country  role  EC contrib. [€] 
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
List of publications.
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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