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Today's Topics:
1. Two open positions at Zuse Institute Berlin, Mathematical
Optimization Methods (Ambros Gleixner)
2. CFP: Ieee CEC2017 Special
SessiononModelReductioninMulti-Objective and Robust Design
Optimization (Hou Liqiang)
3. CfP: LION 11, Eleventh Learning and Intelligent Optimization
Conference (Thomas Stuetzle)
4. Two postdoc positions in Warwick (Dan Kral)
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Message: 1
Date: Fri, 25 Nov 2016 02:38:09 +0100
From: Ambros Gleixner <gleixner@zib.de>
To: dmanet@zpr.uni-koeln.de
Subject: [DMANET] Two open positions at Zuse Institute Berlin,
Mathematical Optimization Methods
Message-ID: <1c5b375e-8ec2-2761-1b3d-84c6f7700306@zib.de>
Content-Type: text/plain; charset=utf-8; format=flowed
PostDoc and PhD positions available at Zuse Institute Berlin
The research group Mathematical Optimization Methods at Zuse Institute
Berlin is currently looking for outstanding candidates to fill two open
positions:
*** WA 28/16: a PhD track research position (100% TV-L E13) ***
on the topic of high-precision mixed-integer programming over the
rational numbers, see http://www.zib.de/node/2664
*** WA 29/16: a PostDoc researcher position (100% TV-L E14) ***
with self-defined research agenda in the context of computational
mixed-integer linear programming, see http://www.zib.de/node/2688
Our group holds longstanding expertise in the design and implementation
of mathematical optimization solvers and you will be part of the
research team around the SCIP Optimization Suite (http://scip.zib.de/).
We expect creativity and a high degree of team spirit and commitment to
problem solving. We offer a friendly working atmosphere, excellent
equipment, and a challenging professional environment. Due to our
involvement in major regional cooperative projects, such as the Einstein
Center for Mathematics (ECMath), the Matheon Research Center, the Berlin
Mathematical School (BMS) or the Berlin Big Data Center (BBDC), we have
close ties to universities and research institutes in the region. We
offer scientists in all career stages opportunities for further
qualification and strongly support research on top level with
international visibility.
We are committed to an active onboarding process to facilitate new
members with all the tools and the knowledge they need for success in
our institute and their career. We provide a family-friendly work
environment through flexible working hours and meeting times and the
opportunity for part-time working arrangements.
The starting date is from March 1, 2017, and can be negotiated. For more
details, please consult the official job postings at
and
Please don't hesitate to contact me if you have any questions regarding
the positions.
Best regards,
Ambros Gleixner
------------------------------
Message: 2
Date: Fri, 25 Nov 2016 10:45:30 +0800 (CST)
From: Hou Liqiang <houliqiang2008@139.com>
To: dmanet <dmanet@zpr.uni-koeln.de>
Subject: [DMANET] CFP: Ieee CEC2017 Special
SessiononModelReductioninMulti-Objective and Robust Design
Optimization
Message-ID:
<2b165837a480cc1-00013.Richmail.00007215005027891531@139.com>
Content-Type: text/plain;charset=UTF-8
* Apologies if you received multiple copies
* Please kindly forward to those who may be interested.
***
IEEE Congress on Evolutionary Computation 2017, Donostia - San Sebastián, Spain, June 5-8, 2017
***
Special Session on Model Reduction in Multi-Objective and Robust Design Optimization
https://sites.google.com/site/adloptimization/home
***
Submission deadline: January 16, 2017.
***
IEEE CEC 2017 is a world-class conference that aims to bring together researchers and practitioners in the field of evolutionary computation and computational intelligence from all around the globe. The special session aims to promote research on theoretical and practical aspects of multi-objective optimization, surrogate assisted optimization and robust design optimization, etc.
*Scope and Motivations*
With model reduction, e.g. Proper Orthogonal Decomposition (POD, also called Principal Components Analysis, PCA) based model reduction, expenses of optimization process can be greatly reduced. Take the standard ZDT series test functions for example, it takes around 20 iterations for the MOO with POD model reduction to search the true Pareto front. The model reduction can also be used in surrogate assisted optimization and evidence approximation. With model reduction, surrogate and evidence computation can be constructed on a reduced data set, thus the sample size can be greatly reduced.
The optimization with model reduction shows advantages over conventional MOOs and can be potentially extended to the scenarios such as optimization problems with many objectives. However, to implement successfully the methods in design optimization with expensive model under uncertainty, a series of issues such as evidence approximation, model fidelity management, optimization algorithm and the strategy to integrate them, etc. should be resolved. We therefore propose the special issue on Model Reduction in Multi-objective and Robust Optimization.
Scope and Topic:
The session seeks to promote discussion and presentation of related novel works. Topics may include, but are not limited to:
Multi-objective optimization Many-objective optimization Robust design optimization Multi-Fidelity optimization Uncertainty modeling Parameter reduction Data mining in Multi-objective and Many-objective Optimization Model fidelity management Surrogate of expensive model Model reduction in Multi-objective and Many-objective Optimization Infill strategy of surrogate Surrogate assisted optimization Evidence approximation of epistemic uncertainty Multi-objective robust optimization under uncertainty Applications of design optimization with model reduction, particularly the aerospace engineering design Preliminary space mission design under uncertainty Multi-objective optimization in preliminary space mission design
Important date
Deadline for contribution paper submission: January 16, 2017. Notification of acceptance: February 26, 2017 Final paper submission: March 12, 2017 Conference dates: June 5-8, 2017
Organizers
Dr. Liqiang Hou, State Key Laoratory of Astronautic Dynamics, Xi'an Staellite Control Center, Xi'an, China Dr. Tapabrata Ray, School of Engineering and Information Technology University of New South Wales, Canberra, Australia Dr. Edmondo Minisci, Department of Mechanical & Aerospace Engineering of University of Strathclyde, Glasgow, UK
------------------------------
Message: 3
Date: Fri, 25 Nov 2016 13:53:26 +0100
From: Thomas Stuetzle <stuetzle@ulb.ac.be>
To: dmanet@zpr.uni-koeln.de
Subject: [DMANET] CfP: LION 11, Eleventh Learning and Intelligent
Optimization Conference
Message-ID: <C865C1B4-D9A8-4E11-8EBB-FD7340BC8EDC@ulb.ac.be>
Content-Type: text/plain; charset=us-ascii
===== CALL FOR PAPERS =====
LION 11, Eleventh Learning and Intelligent Optimization Conference
Submission deadline: December 18, 2016
Conference dates: 19-21 June, 2017
Conference location: Nizhny Novgorod, Russia
More info: http://intelligent-optimization.org/lion11/
===== Scope =====
Practitioners using heuristic algorithms for hard optimization problems are confronted with the burden of selecting the most appropriate method, in many cases through expensive algorithm configuration and parameter tuning. Scientists seek theoretical insights and demand a sound experimental methodology for evaluating algorithms and assessing strengths and weaknesses. This effort requires a clear separation between the algorithm and the experimenter, who, in too many cases, is "in the loop" as a motivated intelligent learning component. LION deals with designing and engineering ways of "learning" about the performance of different techniques, and ways of using past experience about the algorithm behavior to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained online or offline can improve the algorithm design process and simplify the applications of high-performance optimization methods. Combinations of different algorithms can further improve the robustness and performance of the individual components.
This meeting, which continues the successful LION series, explores the intersections and uncharted territories between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. Russia has a long tradition in optimization theory, computational mathematics and "intelligent learning techniques" (in particular cybernetics and statistics). The location of LION11 in Nizhny is an occasion to meet researchers and consolidate research and human links. In internet time the value of a conference must go well beyond presenting scientific papers. In particular, we are discussing and planning:
- Contests in continuous and discrete optimization.
- Sessions dedicated to commercial software and open source initiatives.
- Parallel computing, supercomputing, and cloud for "big optimization".
- Elevator pitches about new and crazy ideas (also by PhD students).
- Tutorials about methods and software.
===== Submission Instructions =====
Please prepare your paper in English using the Lecture Notes in Computer Science (LNCS) template. Papers must be submitted in PDF.
Types of Submissions
When submitting a paper to LION11, authors are required to select one of the following three types of papers:
* Long paper: original novel and unpublished work (max. 15 pages in LNCS format);
* Short paper: an extended abstract of novel work (max. 6 pages in LNCS format);
* Work for oral presentation only (no page restriction; any format). For example, work already published elsewhere, which is relevant and which may solicit fruitful discussion at the conference.
===== Publication Details =====
Post-conference proceedings are published by Springer-Verlag in its LNCS series. A special issue of a scientific journal with invited extended version of the best papers is being planned.
===== Further Information =====
Up-to-date information will be published on the web site
http://intelligent-optimization.org/lion11/. For information
about local arrangements, registration forms, etc., please refer to the
above-mentioned web site or contact the local organizers.
LION 11 will be collocated with the 7th International Conference on Network Analysis (June 22-24, 2017).
===== Important Dates =====
Submission deadline December 18, 2016
Notification of acceptance March 10, 2017
Conference June 19-21, 2017
===== LION 11 Committee =====
General Chair
Yaroslav Sergeyev, University of Calabria (Italy) and Lobachevsky University, Nizhny (Russia).
Local organization committee
Roman Strongin (Chair), Victor Kasantsev (Vice-Chair), Victor Gergel (Vice-Chair), Vladimir Grishagin, Dmitri Balandin, Konstantin Barkalov, Dmitri Kvasov.
Steering committee
Roberto Battiti (head), Holger Hoos, Youssef Hamadi, Mauro Brunato, Thomas Stuetzle, Christian Blum, Martin Charles Golumbic, Marc Schoenauer, Xin Yao, Benjamin W. Wah.
------------------------------
Message: 4
Date: Fri, 25 Nov 2016 14:06:56 +0000
From: Dan Kral <D.Kral@warwick.ac.uk>
To: dmanet@zpr.uni-koeln.de
Subject: [DMANET] Two postdoc positions in Warwick
Message-ID:
<CAO6OfRFH2DWdteNe2BprLbxBNJbHq+4TLgSM1PSN1Fn1ZKQcKQ@mail.gmail.com>
Content-Type: text/plain; charset=UTF-8
Dear colleagues,
we are advertising two postdoc positions in combinatorics with a particular
focus on combinatorial limits and extremal combinatorics. However no
previous experience with research in these areas is required; applications
from recent PhD graduates are particularly welcome.
One of the positions is EPSRC-funded and the other is ERC-funded. The
expected starting date is October 2017 but the exact starting date of the
24-month ERC-funded position can be negotiated. The closing date for
applications to the positions is January 5, 2017. I enclose links with
further details.
http://www.jobs.ac.uk/job/AVS801/research-fellow-78754-116/
http://www.jobs.ac.uk/job/AVS865/research-fellow-78755-116/
Best regards,
Dan Kral
------------------------------
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