Engineering Cyber-physical information gathering and utilizing
systems(CIGUS) presents the systems engineer with a difficult,
multi-criterion, multi-objective decision problem. Research, development
and design is done over many disciplines, across many domains, each
with their specific models. Systems engineers are expected to provide a
common level of communication amongst the domains to promote convergence
to a design. We present novel information measures that enable
combination of the underlying domain specific subsystems parameters
in a way that makes the information yield of the system intelligible to
decision makers and domain experts. These measures enable, for the
first time, the application of multi-objective evolutionary algorithms and
end-to-end computer aided engineering of CIGUS.
Our novel approach is validated and verified through the application
and direct comparison of simulated and experimental results of state-ofthe-
art weather radar network test bed designs. The approach resulted
in Pareto optimal point within an average of 10% of the actual case
study design parameters and within 25% of the Pareto ideal point.
No additional parameters beyond the underlying domain parameters
were introduced. This demonstrates that the computationally aided
engineering approach presented in this work facilitates engineering
feasibility decisions and the subsequent evolution of the engineered
systems in way that reduces cost and effort.