The development of powerful search and optimization techniques is of great importance in science and engineering, particularly in today's world that requires researchers to tackle growing needs in health care, big data, energy conservation and the design of new smart cities, to name just a few.
In general, we see two well-established fields that are addressing these issues, (i) traditional numerical optimization techniques and (ii) bio-inspired heuristic methods. Both general approaches have unique strengths and weaknesses, allowing researchers to solve some challenging problems but still fail in others.
The goal of NEO is to bring together people from both fields to discuss, compare and merge these complimentary perspectives, to help in the development of collaborative work that might allow researchers to maximize the strengths and to minimize the weaknesses of both paradigms.
Moreover, NEO intends to help researchers in these fields understand real-world problems that might benefit from such algorithms, particularly in pressing issues that affect us all: health care, smart cities, big data, among others.
NEO invites researchers to present their work, encouraging original contributions but also accepting presentations of previously-published works that fit into the NEO´s objective.
Topics of interest include:
Search and Optimization:
Single- and multi-objective optimization
Advances in Evolutionary Algorithms and Genetic Programming