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Parallel Problem Solving from Nature - PPSN XIV - 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings (Paperback, 1st ed. 2016)
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Parallel Problem Solving from Nature - PPSN XIV - 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings (Paperback, 1st ed. 2016)
Series: Theoretical Computer Science and General Issues, 9921
Expected to ship within 10 - 15 working days
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This book constitutes the refereed proceedings of the 14th
International Conference on Parallel Problem Solving from Nature,
PPSN 2016, held in Edinburgh, UK, in September 2016. The total of
93 revised full papers were carefully reviewed and selected from
224 submissions. The meeting began with four workshops which
offered an ideal opportunity to explore specific topics in
intelligent transportation Workshop, landscape-aware heuristic
search, natural computing in scheduling and timetabling, and
advances in multi-modal optimization. PPSN XIV also included
sixteen free tutorials to give us all the opportunity to learn
about new aspects: gray box optimization in theory; theory of
evolutionary computation; graph-based and cartesian genetic
programming; theory of parallel evolutionary algorithms; promoting
diversity in evolutionary optimization: why and how; evolutionary
multi-objective optimization; intelligent systems for smart cities;
advances on multi-modal optimization; evolutionary computation in
cryptography; evolutionary robotics - a practical guide to
experiment with real hardware; evolutionary algorithms and
hyper-heuristics; a bridge between optimization over manifolds and
evolutionary computation; implementing evolutionary algorithms in
the cloud; the attainment function approach to performance
evaluation in EMO; runtime analysis of evolutionary algorithms:
basic introduction; meta-model assisted (evolutionary)
optimization. The papers are organized in topical sections on
adaption, self-adaption and parameter tuning; differential
evolution and swarm intelligence; dynamic, uncertain and
constrained environments; genetic programming; multi-objective,
many-objective and multi-level optimization; parallel algorithms
and hardware issues; real-word applications and modeling; theory;
diversity and landscape analysis.
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