Applications in Constrained Optimization

Calculus: Applications in Constrained Optimization provides an accessible yet mathematically rigorous introduction to constrained optimization, designed for undergraduate students who have some experiences with multivariable calculus. Based on a successful course at National Taiwan University (NTU) ── Calculus 4: Applications in Economics and Management, this book connects foundational calculus with contemporary techniques of optimization used in economics, management, and data science.Classical tools such as Lagrange multipliers and second derivative tests are extended into a general framework that covers both equality and inequality constraints. Readers will also learn to identify degenerate cases and apply second-order conditions in multivariable settings. Key concepts from linear algebra are introduced and integrated throughout.Each chapter concludes with a carefully structured set of exercises:● Type (A) questions test basic understanding;● Type (B) questions reinforce key example

This volume provides a broad and uniform introduction of PDE-constrained optimization as well as to document a number of interesting and challenging applications. Many science and engineerin

This book introduces, in an accessible way, the basic elements of Numerical PDE-Constrained Optimization, from the derivation of optimality conditions to the design of solution algorithms. Numerical o

Optimization problems subject to constraints governed by partial differential equations (PDEs) are among the most challenging problems in the context of industrial, economical and medical applications

This thesis presents a wholly new technique in the structural analysis of data that uses a ‘greedy’ algorithm to derive optimal sparse solutions, enabling faster and more accurate results in formerly

In a constrained optimization problem, the decisionmaker wants to select the “optimal” choice – the one most valuable to him or her – that also meets all of the constraints imposed by the problem. Suc

In a constrained optimization problem, the decisionmaker wants to select the “optimal” choice – the one most valuable to him or her – that also meets all of the constraints imposed by the problem. Suc

Clustering algorithms take data with any number of dimensions and group them into subsets so each member of a subset is near the other members in some sense. In 17 articles including an introduction,

Organizations and businesses strive toward excellence, and solutions to problems are based mostly on judgment and experience. However, increased competition and consumer demands require that the solutions be optimum and not just feasible. Theory leads to algorithms. Algorithms need to be translated into computer codes. Engineering problems need to be modeled. Optimum solutions are obtained using theory and computers, and then interpreted. Revised and expanded in its third edition, this textbook integrates theory, modeling, development of numerical methods, and problem solving, thus preparing students to apply optimization to real-world problems. This text covers a broad variety of optimization problems using: unconstrained, constrained, gradient, and non-gradient techniques; duality concepts; multi-objective optimization; linear, integer, geometric, and dynamic programming with applications; and finite element-based optimization. It is ideal for advanced undergraduate or graduate cours

"It is vitally important to meet or exceed previous quality and reliability standards while at the same time reducing resource consumption. This textbook addresses this critical imperative integrating

Andreas Potschka discusses a direct multiple shooting method for dynamic optimization problems constrained by nonlinear, possibly time-periodic, parabolic partial differential equations. In contrast t

A comprehensive treatment of semismooth Newton methods in function spaces: from their foundations to recent progress in the field. This book is appropriate for researchers and practitioners in PDE-con

This book constitutes the refereed proceedings of the 4th International Conference on Combinatorial Optimization and Applications, COCOA 2010, held in Kailua-Kona, HI, USA, in December 2010.The 49 rev

"It is vitally important to meet or exceed previous quality and reliability standards while at the same time reducing resource consumption. This textbook addresses this critical imperative integrating

This book constitutes the refereed proceedings of the 4th International Conference on Combinatorial Optimization and Applications, COCOA 2010, held in Kailua-Kona, HI, USA, in December 2010.The 49 rev

This volume presents a collection of recent studies covering the spectrum of computational intelligence applications with emphasis on their application to challenging real-world problems. Topics cover

The 21 self-contained chapters in this book, include recent developments in several optimization-related topics such as decision theory, linear programming, turnpike theory, duality theory, convex an

The origin of any industrial optimization study lies in the theory that some improvement can be made in a controllable system. The possibility for improvements may arise in any context, for example, i

A thorough and highly accessible resource for analysts in a broad range of social sciences. Optimization: Foundations and Applications presents a series of approaches to the challenges faced by anal

Optimization principles are of undisputed importance in modern design and system operation. They can be used for many purposes: optimal design of systems, optimal operation of systems, determination o