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Synergy for Smart Multi-Objective Optimisation

Total Cost €


EC-Contrib. €






Project "SYNERGY" data sheet

The following table provides information about the project.


Organization address
address: Jamova 39
postcode: 1000

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 Slovenia [SI]
 Project website
 Total cost 1˙016˙890 €
 EC max contribution 1˙016˙890 € (100%)
 Programme 1. H2020-EU.4.b. (Twinning of research institutions)
 Code Call H2020-TWINN-2015
 Funding Scheme CSA
 Starting year 2016
 Duration (year-month-day) from 2016-02-01   to  2019-01-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    INSTITUT JOZEF STEFAN SI (LJUBLJANA) coordinator 489˙875.00
2    TECHNISCHE HOCHSCHULE KOLN DE (KOLN) participant 266˙412.00
3    UNIVERSITE DE LILLE FR (LILLE) participant 260˙602.00


 Project objective

Many real-world application areas, such as advanced manufacturing, involve optimisation of several, often time-consuming and conflicting objectives. For example, they require the maximisation of the product quality while minimising the production cost, and rely on demanding numerical simulations in order to assess the objectives. These, so-called multi-objective optimisation problems can be solved more efficiently if parallelisation is used to execute the simulations simultaneously and if the simulations are partly replaced by accurate surrogate models. The overall goal of the SYNERGY project is to overcome the limitations of the current initial-stage research in multi-objective optimization at the Jožef Stefan Institute (JSI), Ljubljana, Slovenia, where efficiency measures have only been explored at a very small scale and with no collaboration with other partners. To that end, JSI initiates this project with two high-profile research institutions with complementary expertise, Université des sciences et technologies de Lille (USTL), France, and Cologne University of Applied Sciences (CUAS), Germany. While USTL is a leading partner in parallelisation on large-scale heterogeneous architectures, CUAS provides expertise in surrogate modelling and its deployment in optimisation problems. The project addresses three core objectives: (1) improve JSI excellence and unleash its research and innovation potential through training in parallelisation and surrogate modelling, and aiding organisation of workshops that will foster discovery of new ways of combining the two methods; (2) raise the research profile of JSI staff and broaden its recognition through networking that will result in knowledge transfer, joint publications and future research projects; and (3) increase the overall research and innovation potential of Slovenia by disseminating the acquired knowledge to other Slovenian research organisations, and deploying it in future applied projects.


List of deliverables.
Proceedings of the BIOMA conference Documents, reports 2019-10-29 12:11:58
Report on refining surrogate modelling Documents, reports 2019-10-29 12:11:58
Report on improving excellence in multi-objective optimisation Documents, reports 2019-10-29 12:11:58
Conference proceeding of the HPO in industry conference Documents, reports 2019-10-29 12:11:58
Edited book on high-performance optimisation Documents, reports 2019-10-29 12:11:58
Report on enhancing high-performance computing Documents, reports 2019-10-29 12:11:58
Summer school course materials Documents, reports 2019-10-29 12:11:58
Potential complex optimisation problems in science and industry Documents, reports 2019-10-29 12:11:58
Report on prepared key performance indicators Documents, reports 2019-10-29 12:11:57
Tutorial on parallel multi-objective optimisation Documents, reports 2019-10-29 12:11:57
Project website Websites, patent fillings, videos etc. 2019-10-29 12:11:57
Tutorial on surrogate-assisted modelling Documents, reports 2019-10-29 12:11:57

Take a look to the deliverables list in detail:  detailed list of SYNERGY deliverables.


year authors and title journal last update
List of publications.
2017 Tušar , Tea; Hansen , Nikolaus; Brockhoff , Dimo
Anytime Benchmarking of Budget-Dependent Algorithms with the COCO Platform
published pages: , ISSN: , DOI: 1 2019-10-29
2018 Gregor Papa, Gašper Petelin, and Peter Korošec
Evolution of electric motor design approaches : the domel case
published pages: , ISSN: , DOI:
Mednarodna konferenca o visokozmogljivi optimizaciji v industriji, HPOI 2018 : zbornik 21. mednarodne multikonference Informacijska družba - IS 2018 2019-10-29
2019 Tome Eftimov, Peter Korošec
A novel statistical approach for comparing meta-heuristic stochastic optimization algorithms according to the distribution of solutions in the search space
published pages: 255-273, ISSN: 0020-0255, DOI: 10.1016/j.ins.2019.03.049
Information Sciences 489 2019-10-29
2018 Gregor Papa and Peter Korošec
From a production scheduling simulation to a digital twin
published pages: , ISSN: , DOI:
Mednarodna konferenca o visokozmogljivi optimizaciji v industriji, HPOI 2018 : zbornik 21. mednarodne multikonference Informacijska družba - IS 2018 2019-10-29
2017 Tea Tu?ar, Klemen Gantar, Valentin Koblar, Bernard ?enko, Bogdan Filipi?
A study of overfitting in optimization of a manufacturing quality control procedure
published pages: 77-87, ISSN: 1568-4946, DOI: 10.1016/j.asoc.2017.05.027
Applied Soft Computing 59 2019-10-29
2018 Gregor Papa, Peter Korošec, Gašper Petelin
Evolution of Electric Motor Design Approaches: The Domel Case
published pages: 57, ISSN: 2348-442X, DOI: 10.6025/tmd/2018/6/2/47-56
Transactions on Machine Design (TMD) 6/2 2019-10-29

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