Bøger i Nonconvex Optimization and Its Applications serien

Studies a different type of eigenvalue problem, one that is very useful for applications: eigenvalue problems related to hemivariational inequalities, that is involving nonsmooth, nonconvex, energy functions. This book also studies nonresonant and resonant cases both for static and dynamic problems.

Hemivariational inequalities represent an important class of problems in nonsmooth and nonconvex mechanics. The present book gives a rigorous analysis of finite element approximation for a class of hemivariational inequalities of elliptic and parabolic type.

This collection of challenging and well-designed test problems arising in literature studies also contains a wide spectrum of applications, including pooling/blending operations, heat exchanger network synthesis, homogeneous azeotropic separation, and dynamic optimization and optimal control problems.

As its title implies, Advances in Multicriteria Analysis presents the most recent developments in multicriteria analysis and in some of its principal areas of application, including marketing, research and development evaluation, financial planning, and medicine.

We not only anticipate that there will be neural computers with intelligence but we also believe that the research results of artificial neural networks might lead to new algorithms on von Neumann's computers.

Linking singularity and transversality theory with non-smooth optimization, this book examines complementarity-constrained mathematical programs, semi-infinite programming problems, mathematical programs with vanishing constraints, and bi-level optimization.

This contributed volume consists of papers in the area of nonconvex optimization from researchers practicing in India. It aims to bring together new concepts, theoretical developments, and applications from these researchers.

Presenting information concerning quasidifferentiability and related topics, this book is a collection of results in different aspects of nonsmooth analysis related to, connected with or inspired by quasidifferential calculus. It is useful for specialists in optimization, mathematical programming, convex analysis, and nonsmooth analysis.

Semi-infinite programming (briefly: SIP) is an exciting part of mathematical programming. The theory in SIP as well as the number of numerical SIP methods and appli cations have expanded very fast during the last years.

In the paper we propose a model of tax incentives optimization for inve- ment projects with a help of the mechanism of accelerated depreciation. Unlike the tax holidays which influence on effective income tax rate, accelerated - preciation affects on taxable income.

Industrial, financial, commercial or any kinds of project have at least one common feature: the better organized they are, the higher the profit or the lower the cost. Project management is the principle of planning different projects and keeping them on track within time, cost and resource constraints.

Offers a comprehensive mathematical theory of duality for general non-convex, non-smooth systems, with emphasis on methods and applications in engineering mechanics. This book covers topics such as the classical (minimax) mono-duality of convex static equilibria, the bi-duality in dynamical systems, and the tri-duality in non-convex problems.

This book deals with decision making in environments of significant data un certainty, with particular emphasis on operations and production management applications.

Completion of such an algorithm with a list of solutions constitutes a rigorous mathematical proof that all of the solutions within the original search region are within the output list. The monograph is appropriate as an introduction to research and technology in the area, as a desk reference, or as a graduate-level course reference.

This collection of challenging and well-designed test problems arising in literature studies also contains a wide spectrum of applications, including pooling/blending operations, heat exchanger network synthesis, homogeneous azeotropic separation, and dynamic optimization and optimal control problems.

Bilevel programming problems are hierarchical optimization problems where the constraints of one problem (the so-called upper level problem) are defined in part by a second parametric optimization problem (the lower level problem).

Focuses on deterministic methods and stochastic methods for global optimization, distributed computing methods in global optimization, and applications of global optimization in several branches of applied science and engineering, computer science, computational chemistry, structural biology, and bio-informatics.

Semi-infinite programming (SIP) deals with optimization problems in which either the number of decision variables or the number of constraints is finite. This book presents the state of the art in SIP in a suggestive way, bringing the powerful SIP tools close to the potential users in different scientific and technological fields.

The aim of the book is to cover the three fundamental aspects of research in equilibrium problems: the statement problem and its formulation using mainly variational methods, its theoretical solution by means of classical and new variational tools, the calculus of solutions and applications in concrete cases.

Mathematical Programming has been of significant interest and relevance in engineering, an area that is very rich in challenging optimization problems. In particular, many design and operational problems give rise to nonlinear and mixed-integer nonlinear optimization problems whose modeling and solu tion is often nontrivial.

This book details algorithms for large-scale unconstrained and bound constrained optimization. It shows optimization techniques from a conjugate gradient algorithm perspective as well as methods of shortest residuals, which have been developed by the author.

Probabilistic and percentile/quantile functions play an important role in several applications, such as finance (Value-at-Risk), nuclear safety, and the environment.

Interest in constrained optimization originated with the simple linear pro gramming model since it was practical and perhaps the only computationally tractable model at the time.

Offers a discussion of mathematical topics including variational and hemivariational inequalities, duality, complementarity, variational principles, sensitivity analysis, eigenvalue and resonance problems, and minimax problems. This book considers applications in different areas such as nonsmooth statics and dynamics.

Experience gained during a ten-year long involvement in modelling, program ming and application in nonlinear optimization helped me to arrive at the conclusion that in the interest of having successful applications and efficient software production, knowing the structure of the problem to be solved is in dispensable.

In the Reformulation Phase, certain types of additional implied polynomial constraints, that include the aforementioned constraints in the case of binary variables, are appended to the problem.

Multiple objective programming deals with the extension of optimization techniques to account for several objective functions, while game theory deals with the inter-personal dynamics surrounding conflict.

In the early fifties, applied mathematicians, engineers and economists started to pay c10se attention to the optimization problems in which another (lower-Ievel) optimization problem arises as a side constraint.