Various discrete and continuous optimization problems are challenge for modern Computer Science and Mathematics. Processing such tasks require sufficient computational resources, time and energy. Since most complex and real world problems are not amenable for exact algorithms, approximation algorithms can be used instead.
Many algorithms aim finding an acceptable (or near optimal) solution, utilizing limited computational resources within acceptable period of time and energy use.
The "Numerical Search and Optimization" special session in NM&A 2018 focuses on theoretical and applied advances in the field of search and optimization. It aims to provide a forum for researchers and developers to exchange the latest experiences, ideas and results on various methods to cross-fertilize domains of algorithms, software implementations, computational science, complex applications, and multidimensional, constrained and global tasks.
Works matching this general statement are welcomed, not only in the mentioned topics but also in other related fields.