Third-party references to IOSO Optimization Technology

Dear Colleagues,

We would like to offer you some third-perty references to IOSO optimization technology from well-known scientists in this area

George S. Dulikravich, Florida International University
AFOSR - Air Force Office of Scientific Research, US:

Page 2
Currently,
a Russian commercially available software named IOSO is the most
efficient and the most robust multi-objective optimization software…
IOSO, which involves concepts of neural networks, radial basis
functions, and self-adapting response surface methodologies, requires
the minimum number of the objective function evaluations and that is
the most versatile and robust multi-objective optimizer.  Details…

Timothy W. Simpson, The Pennsylvania State University, US
Vasilli Toropov, University of Leeds, UK

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IOSO
offers unique state of the art optimization algorithms that are based
on self-organizational strategy and efficiently combine traditional
response surface methodology with gradient-based optimization and
evolutionary algorithms in a single run. The offered algorithms are
equally efficient for the problems of complex and simple topology that
may include mixed types of variables. Details...

Carlos A. Coello Coello and Ricardo Landa Becerra
Evolutionary Computation Group Departamento de Computación, Mexico

6.5 Design of alloys
IOSO
consists of two stages. In the first stage, an approximate model of the
objective functions is created. In the second stage, this approximate
model is optimized. IOSO incorporates evolutionary algorithms, and
artificial neural networks with radial basis functions that are used to
build the response surfaces. The idea is to use this metamodel (or
approximate model) to perform a very reduced number of evaluations of
the actual objective functions of the problem. Details...

http://www.iosotech.com/product.htm#Third-party