CALL FOR ABSTRACTS & PARTICIPATION
WORKSHOP on (Multimodal) Multi-Objective Optimization: Challenges,
Characteristics, and Peculiarities
-- as part of the hybrid PPSN 2020 in Leiden (The Netherlands) & online --
Scope of the Workshop
=====================
In practical applications, multi-objective (MO) optimization is usually
treated secondarily due to its rather deterrent complexity/difficulty
(compared to single-objective (SO) optimization problems). Therefore,
practitioners in general scalarize their problems, e.g., by optimizing
weighted sums of the underlying objectives. A major reason for such
behavior is the much lesser tangibility of MO problems; it is extremely
challenging to imagine interaction effects between >= 2 decision
variables and >= 2 objectives simultaneously (let alone visualize them
within a single plot).
Even researchers usually limit themselves to visualizing only the Pareto
fronts of MO problems, i.e., the image of the set of MO global optima.
As a result, our "knowledge" about MO problems is highly influenced by
our understanding of SO problems. For instance, it is well-known that
multimodality can be very challenging in SO optimization. Thus, for a
long time, research simply inferred that such structures cause similar
problems for optimizers in the MO setting. In consequence, such
structures have regularly been considered for the design of MO benchmark
problems. Yet, recent works have shown that multimodality might in fact
even facilitate MO optimization.
Topics of Interest
==================
In an attempt to reduce our knowledge deficit in this particular domain,
the proposed workshop shall provide a platform for researchers to
actively exchange ideas that improve our understanding of (multimodal)
MO continuous optimization problems. We therefore welcome contributions
related to the following non-exclusive list of topics:
-> Characteristics of continuous and combinatorial MO optimization
problems.
-> High-level landscape characteristics (such as ridges, plateaus,
etc.) as well as exploratory landscape features.
-> Empirical and theoretical results on the transferability of
structural properties from SO to MO problems.
-> Multiobjectivization strategies for SO problems.
-> Techniques for visualizing landscapes of (multimodal) MO problems.
-> Algorithms and/or algorithm building blocks (e.g., operators,
selection mechanisms) that are capable of handling or exploiting
discovered challenges in problem structures (such as multimodality,
ill-conditioned landscapes, etc.).
-> Consequences for the design of benchmark problems and evaluation of
existing test problem suites.
How to Contribute?
==================
If you want to contribute actively with a 10 minutes spotlight talk (+20
minutes discussion), please provide an abstract (max. 2 pages) on your
topic until July 26, 2020. Please send your abstract via email to
[log in to unmask] [log in to unmask] The
organizers will check the fit of the proposed topic and schedule the talk.
Important Dates
===============
-> Abstract submission (via email to
[log in to unmask] [log in to unmask]): July 26, 2020
-> Notification of acceptance: August 7, 2020
-> Publication of Program: August 21, 2020
-> Workshop (at PPSN 2020): September 5 or 6, 2020
Workshop Organizers
===================
Christian Grimme, University of Münster, Germany,
[log in to unmask]
Pascal Kerschke, University of Münster, Germany, [log in to unmask]
Heike Trautmann, University of Münster, Germany,
[log in to unmask]
Michael T.M. Emmerich, LIACS, Leiden University, The Netherlands,
[log in to unmask]
Hao Wang, LIACS, Leiden University, The Netherlands,
[log in to unmask]
Further Notes
=============
Please help us raising awareness for this workshop and distribute the
link to this website (http://www.erc.is/go/mmmoo2020).
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