Focussed sessions at LION11
Special sessions are organized as a way to focus submissions and encourage more interaction between
specific communities. In general, submission and publication rules are the same as for the general call for papers,
with the organizers of the special sessions coordinating and helping in identifying competent reviewers.
Pls direct proposals for special session to the general chair: Yaroslav D. Sergeyev: yaro ((AT)) dimes.unical.it .
--- Session 0 --- GENOPT Generalization-based contest in global optimization ---
Roberto Battiti, Head of LIONlab for "Machine Learning and Intelligent Optimization", University of Trento (Italy);
Mauro Brunato, LIONlab, University of Trento (Italy);
Yaroslav Sergeyev, Head of Numerical Calculus Laboratory, University of Nizhny Novgorod (Russia); DIMES, University of Calabria (Italy);
Dmitri Kvasov, University of Nizhny Novgorod (Russia); DIMES, University of Calabria (Italy).
While comparing results on benchmark functions is a widely used practice to demonstrate the competitiveness of
global optimization algorithms, fixed benchmarks can lead to a negative data mining process. The motivated researcher
can "persecute" the algorithm choices and parameters until the final designed algorithm "confesses" positive results for the specific benchmark.
With a similar goal, to avoid the negative data mining effect, the GENOPT contest will be based on randomized function generators,
with fixed statistical characteristics but individual variation of the generated instances.
The generators will be made available to the participants to test offline and online tuning schemes, but the final competition will be based on random seeds communicated in the last phase.
A dashboard will reflect the current ranking of the participants, who are encouraged to exchange preliminary results and opinions.
The final "generalization" ranking will be confirmed in the last competition phase.
Tentative schedule: to be announces Sep 2016, together with new benchmark functions
After LION: special issue of good-quality journal dedicated to results obtained by the reviewed and winning papers.
For further information, visit genopt.org
--- Session 1 --- Large Scale Nonlinear Programming ---
Fasano Giovanni ( fasano ((AT)) unive.it )
Roma Massimo ( roma ((AT)) dis.uniroma1.it )
Caliciotti Andrea ( caliciotti ((AT)) dis.uniroma1.it )
The session proposes a discussion on recent advances of Nonlinear Programming, including promising research topics in both constrained and unconstrained optimization.
The contribution of both expert scientists and researchers, as well as practitioners, is welcome. Possible topics for presentations include, but are not limited to:
- applications of nonlinear optimization,
- nonlinear programming methods,
- parallel algorithms and numerical stability,
- convex and nonconvex optimization over large data sets,
- interior-point methods.
--- Session 2 --- Computational and Optimization Problems of Efficient Data Collection and Transmission ---
Prof. Adil I. Erzin ( adilerzin ((AT)) math.nsc.ru )
Dr. Roman V. Plotnikov ( nomad87 ((AT)) ngs.ru )
Data collection and transmission networks, such as wireless sensor networks, are used in many areas of human activity. Elements of such networks often have a limited supply of non-renewable energy, so energy saving issue is the most important.
Problems of the effective functioning of data collection and transmission networks are reduced to such problems of computational geometry and combinatorial optimization as the problem of constructing optimal covers, to the synthesis of energy efficient communications networks, and to the problems of effective data aggregation.
Rational energy consumption can increase the life time of the network at times. Within the framework of a special session is planned to hear the results regarding new problem formulations, as well as algorithms for solving the above problems.
--- Session 3 --- Large Scale Projection Problems ---
Prof. Evgeni Nurminski, Far Eastern Federal University (Russia) (nurmi ((AT)) dvo.ru )
Finding a least-norm element of a certain set is at the heart of many approaches in automatic classification, machine learning, optimization, computational physics, chemistry, and economics. The size of these problems and their complexity continues to grow up exponentially, overcoming hardware improvements in computing machinery. This certainly calls for algorithmic advances and this session invites interested parties to participate in the discussions on specific projection problems and their applications, as well as new ideas for algorithms. A special attention will be given to solution of structured projection problems, involving decomposition and parallel computations.
--- Session 4 --- Stochastic and deterministic global optimization ---
Prof. Anatoly Zhigljavsky, Cardiff University, (Great Britain) (ZhigljavskyAA ((AT)) cardiff.ac.uk )
Prof. Vladimir Grishagin, Nizhni Novgorod State University (Russia) (vagris ((AT)) unn.ru )
Decision making models formulated as global optimization problems occur in many contemporary real world applications and require for their development significant variety of theoretical, algorithmic, computational, and applied techniques. The scope of the session consists of a versatile consideration of theoretical fundamentals and numerical analysis of global optimization problems in various fields: nonlinear, combinatorial, stochastic programming, multicriterial optimization, optimal control, game theory, approximation, etc. As numerical algorithms are the main tools for solving global optimization problems they are considered in the broad sense including presentation of new efficient techniques, their theoretical substantiation and implementation, generalization to parallel computations on supercomputers and to new paradigms of computations, results of numerical experiments, and solving some applied problems.