Innovization: Discovery of innovative design principles through multiobjective evolutionary optimization

K. Deb, Aravind Srinivasan

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review


In optimization studies, often researchers are interested in finding one or more optimal or near-optimal solutions. In this chapter, we describe a systematic optimization-cum-analysis procedure which performs a task beyond simply finding optimal solutions, but first finds a set of near-Pareto-optimal solutions and then analyses them to unveil salient knowledge about properties which make a solution optimal. The proposed ‘innovization’ task is explained and its working procedure is illustrated on a number of engineering design tasks. The variety of problems chosen in the chapter and the resulting innovations obtained for each problem amply demonstrate the usefulness of the proposed innovization task. The procedure is a by-product of performing a routine multiobjective optimization for a design task and in our opinion portrays an important process of knowledge discovery which may not be possible to achieve by other means.
Original languageEnglish
Title of host publicationMultiobjective problem solving from nature: From concepts to applications
EditorsJ. Knowles, D. Corne, K. Deb
Place of PublicationBerlin
Publication statusPublished - 2008
MoE publication typeA3 Part of a book or another research book

Fingerprint Dive into the research topics of 'Innovization: Discovery of innovative design principles through multiobjective evolutionary optimization'. Together they form a unique fingerprint.

Cite this