The workshop attempts to bring together researchers from evolutionary
computation and related areas who are interested in Multimodal Optimization.
This is a currently forming field, and we aim for a highly interactive and
productive meeting that makes a step forward towards defining it.
The Workshop will provide a unique opportunity to review the advances in the
current state-of-the-art in the field of Niching methods. Further discussion
will deal with several experimental/theoretical scenarios, performance
measures, real-world and benchmark problem sets and outline the possible
future developments in this area. Positional statements, suggestions, and
comments are very welcome!
Population-based meta-heuristic search algorithms such as
Evolutionary Algorithms (EAs) or Swarm Intelligence (SI)
approaches, in their original forms are usually designed
for locating a single global solution. Nevertheless, many
real-world problems are multimodal by nature, i.e.,
multiple satisfactory solutions exist. It may be desirable
to locate many such satisfactory solutions so that a
decision maker can choose one that is most appropriate for
his/her problem domain. Numerous techniques have been
developed in the past for locating multiple optima (global
or local), and most of these are commonly referred to as
niching methods, e.g., crowding, fitness sharing, derating,
restricted tournament selection, clearing, speciation.
Multimodal Optimization is currently undergoing a
resurgence, re-establishing itself as an active research
area that transforms and extends beyond the classic niching
methods. This workshop attempts to bring together
researchers from many subfields of operational research,
evolutionary computation and related areas who are
interested in Multimodal Optimization. The Workshop will
provide a unique opportunity to discuss the advances in the
current state-of-the-art in the field of Niching methods.
We intend to hold the workshop in a very interactive
fashion, emphasizing discussion, exchange and possibly
synthesis of opinions. Prospective topics will include,
but are not limited to:
- Adaptive or parameter-less niching methods
- Benchmarking niching methods, including test functions and performance metrics
- Comparative studies of various niching methods
- Handling the issue of niching parameters in niching methods
- Handling the scalability issue (both dimensionality and modality) in niching methods
- Multiobjective approaches to niching
- Theoretical analysis of niching methods
- Niching methods applied to discrete optimization problems
- Niching methods applied to constrained optimization problems
- Niching methods applied to engineering and other real-world optimization problems
- Niching methods applied to computational expensive optimization problems
Please note that
we are NOT primarily interested in the global optimization
task to find a single solution of a multimodal problem.
We invite authors/participants to submit new ideas, positional statements,
and reviews/summaries/comments on existing work in the field of Multimodal
Optimization in the form of extended abstracts (max 2 pages).
The workshop will take place at PPSN 2018 in September 2018. Researchers
working on finding multiple solutions of multimodal optimization problems
are strongly encouraged to contribute!
This workshop is supported by the IEEE CIS Task Force on Multi-modal Optimization.
