Global Optimization with Non-Convex Constraints

Global Optimization with Non-Convex Constraints

by Roman G. Strongin, Yaroslav D. Sergeyev

Join Readfeed freeFind clubs reading this
Rate this book:

Browse books you can read free on Readfeed

No club is reading this yet — be the first to start one

Start a club free
About
This book presents a new approach to global non-convex constrained optimization. Problem dimensionality is reduced via space-filling curves. To economize the search, constraint is accounted separately (penalties are not employed). The multicriteria case is also considered. All techniques are generalized for (non-redundant) execution on multiprocessor systems. Audience: Researchers and students working in optimization, applied mathematics, and computer science.

Discuss Global Optimization with Non-Convex Constraints with other readers

Join or start a book club for Global Optimization with Non-Convex Constraints on Readfeed. Live chat, shared reading progress, and AI discussion questions — free to get started.

Sign up freeBrowse book clubs

Frequently asked questions

How do I join a book club for Global Optimization with Non-Convex Constraints?

Sign up free on Readfeed, then browse public clubs or start your own club with Global Optimization with Non-Convex Constraints as the current read. Invite friends with a share link and discuss together with live chat and AI discussion questions.

Can I discuss Global Optimization with Non-Convex Constraints with other readers online?

Yes. Readfeed book clubs let you chat live, share progress, and join discussions about Global Optimization with Non-Convex Constraints with readers worldwide — whether your club is virtual, in-person, or hybrid.

Is Readfeed free?

Yes. Creating an account and joining book clubs is free. Sign up to find readers who love the same books and start discussing today.