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In most decision-making and design situations, simultaneously satisfying multiple goals is a trial and error process, and is often inefficient. This trend occurs not only in science and engineering, but also in any discipline involving different people with different intentions, or a single decision-maker with more than one target. Although modeling interactive scenarios between people or groups has long been a topic of the social sciences, the process of systematically optimizing a collection of functions is a relatively new focus within the field of engineering. This process is called…mehr

Produktbeschreibung
In most decision-making and design situations,
simultaneously satisfying multiple goals is a trial
and error process, and is often inefficient. This
trend occurs not only in science and engineering, but
also in any discipline involving different people
with different intentions, or a single decision-maker
with more than one target. Although modeling
interactive scenarios between people or groups has
long been a topic of the social sciences, the process
of systematically optimizing a collection of
functions is a relatively new focus within the field
of engineering. This process is called
multi-objective optimization (MOO). This text
presents a comprehensive review of MOO methods with
an eye towards engineering applications. This
provides not only in a lucid synopsis of theory but
also a thorough user s guide with ready-to-use
formulas and mathematical details. The text can be
used as a practical tool for engineering analysts and
researchers, as well as for those working with
operations research and mathematical systems. It can
also serve as an advanced level graduate text, taking
students from basic concepts, to mathematical
fundamentals, through more advanced methods.
Autorenporträt
Dr. Marler is the Senior Research Scientist at The University of
Iowa's Virtual Soldier Research Program. He is a licensed
professional engineer. Dr. Arora is an F. Wendell Miller
Professor of Engineering in University of Iowa's Departments of
Civil and Environmental Engineering, and Mechanical and
Industrial Engineering.