Global optimization concerns the computation and characterization of global optima of nonlinear functions. Such problems are widespread in the mathematical modelling of real systems in a very wide range of applications and the last 30 years have seen the development of many new theoretical, algorithmic and computational contributions which have helped to solve globally multiextreme problems in important practical applications.
Most of the existing books on optimization focus on the problem of computing locally optimal solutions. Introduction to Global Optimization,...

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. Special attention is paid to the interaction between multicriteria analysis, decision support systems and preference modeling. The five sections of the book cover: methodology; problem structuring; utility assessment; multi-objective optimisation; real world applications.
Audience: Researchers and...

The central idea developed by the contributions to this book is that the split between analytic philosophy and phenomenology - perhaps the most impor tant schism in twentieth-century philosophy - resulted from a radicalization of reciprocal partialities. Both schools of thought share, in fact, the same cultural background and their same initial stimulus in the thought of Franz Brentano. And one outcome of the subsequent rift between them was the oblivion into which the figure and thought of Brentano have fallen. The first step to take in remedying this split is to return to Brentano and to...

Motivation Stochastic Linear Programming with recourse represents one of the more widely applicable models for incorporating uncertainty within in which the SLP optimization models. There are several arenas model is appropriate, and such models have found applications in air- line yield management, capacity planning, electric power generation planning, financial planning, logistics, telecommunications network planning, and many more. In some of these applications, modelers represent uncertainty in terms of only a few seenarios and formulate a large scale linear program which is then solved...

This book is an outgrowth of ideas originating from 1. Kluvanek. Unfortunately, Professor Kluvanek did not live to contribute to the project of writing up in a systematic form, the circle of ideas to which the present work is devoted. It is more than likely that with his input, the approach and areas of emphasis of the resulting exposition would have been quite different from what we have here. Nevertheless, the stamp of Kluvanek's thought and philosophy (but not necessarily his approval) abounds throughout this book. Although the title gives no indication, integration theory in vector spaces...

axiomatic results should be at the heart of such a science. Through them, we should be able to enlighten and scientifically assist decision-making processes especially by: - making that wh ich is objective stand out more c1early from that which is less objective; - separating robust from fragile conc1usions; - dissipating certain forms of misunderstanding in communication; - avoiding the pitfall of illusory reasoning; - emphasizing, once they are understood, incontrovertible results. The difficulties I encountered at the begining of my career as an operations researcher, and later as a...

This work grew out of several years of research, graduate seminars and talks on the subject. It was motivated by a desire to make the technology accessible to those who most needed it or could most use it. It is meant to be a self-contained introduction, a reference for the techniques, and a guide to the literature for the underlying theory. It contains pointers to fertile areas for future research. It also serves as introductory documentation for a Fortran 90 software package for nonlinear systems and global optimization. The subject of the monograph is deterministic, automatically verified...

This book deals with decision making in environments of significant data un- certainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness ap- proach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: - It does not ignore uncertainty and takes a proactive step in response to the fact...

Let us assume that an observation Xi is a random variable (r.v.) with values in 1 1 (1R1, 8 ) and distribution Pi (1R1 is the real line, and 8 is the cr-algebra of its Borel subsets). Let us also assume that the unknown distribution Pi belongs to a 1 certain parametric family {Pi(), () E e}. We call the triple i = {1R1, 8, Pi(), () E e} a statistical experiment generated by the observation Xi. n We shall say that a statistical experiment n = {lRn, 8, P;, () E e} is the product of the statistical experiments i, i = 1, ..., n if PO' = P () X ... X P () (IRn 1 n n is the n-dimensional Euclidean...

The problem of "Shortest Connectivity," which is discussed here, has a long and convoluted history. Many scientists from many fields as well as laymen have stepped on its stage. Usually, the problem is known as Steiner's Problem and it can be described more precisely in the following way: Given a finite set of points in a metric space, search for a network that connects these points with the shortest possible length. This shortest network must be a tree and is called a Steiner Minimal Tree (SMT). It may contain vertices different from the points which are to be connected. Such points are...