Design optimization applies the methods of [[mathematical optimization]] to design problem formulations and it is sometimes used interchangeably with the term [[engineering optimization]]. When the objective function ''f'' is a vector rather than a scalar, the problem becomes a [[multi-objective optimization]] one. If the design optimization problem has more than one mathematical solutions the methods of [[global optimization]] are used to identified the global optimum. Practical design optimization problems are typically solved numerically and many [[:Category:Mathematical optimization software]]{{dn|date=Mayoptimization 2018}}software]] exist in academic and commercial forms<ref>{{Cite book|url=https://books.google.com/books?hl=en&lr=&id=wy5hBwAAQBAJ&oi=fnd&pg=PR17&dq=design+optimization+with+matlab+achille+messac&ots=n9WXaRte_T&sig=DVBwayB-6W1b2YyruSz6O2fMKAM#v=onepage&q=design%20optimization%20with%20matlab%20achille%20messac&f=false|title=Optimization in Practice with MATLAB®: For Engineering Students and Professionals|last=Messac|first=Achille|date=2015-03-19|publisher=Cambridge University Press|isbn=9781316381373|language=en}}</ref>. There are several ___domain-specific applications of design optimization posing their own specific challenges in formulating and solving the resulting problems; these include, [[shape optimization]], [[wing-shape optimization]], [[topology optimization]], [[architectural design optimization]], [[Power optimization (EDA)|power optimization]].
