Optimisation books

I was attracted then by a gap between vector optimization used to serve as a formal model for multiple objective...  Read More >>

Although in recent years it has become viable to solve many large scale discrete optimisation problems some problems...  Read More >>

Focuses on the progress in turnpike theory. This book presents a number of results concerning the turnpike properties...  Read More >>

This volume mark's the centenary of the birth of the outstanding mathematician of the 20th century, Sergey Sobolev....  Read More >>

Here is a much-needed attempt to reconcile optimization with apportionment in just-in-time (JIT) sequences. It argues...  Read More >>

The problems include are nonlinear vector optimization problems, s- metric dual problems, continuous-time vector...  Read More >>

This book examines results of convex analysis and optimization in Hilbert space, presenting a concise exposition...  Read More >>

This book 's two-fold focus provides a broad overview of the varied topics in risk management as well as outlining...  Read More >>

Contains chapters on parts of simulated annealing, tabu search, ant colony algorithms, general purpose studies of...  Read More >>

This book provides a comprehensive study of complexity results and optimal and suboptimal algorithms concerning...  Read More >>

The first part of the book addresses optimisation problems and decision modelling, with special attention to applications...  Read More >>

This book is for a first course in stochastic processes taken by undergraduates or master’s students who have had...  Read More >>

This book details algorithms for large-scale unconstrained and bound constrained optimization. It shows optimization...  Read More >>

Data Mining in Biomedicine  Read More >>

One of the primary purposes of any model is to build intuition and generate insights. This book touches on nine...  Read More >>

Gomory [80] in the late 1950s, the theoretical and methodological development of integer programming has grown by...  Read More >>

Examines Markov Decision Processes - also called stochastic dynamic programming - and their applications in the...  Read More >>

One major insight of this type is the connection between the purely analytical character of an optimization problem,...  Read More >>

Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods...  Read More >>

This book provides an introduction to MIP modeling and to planning systems, a unique collection of reformulation...  Read More >>

In this regard, we refer to the works of Pironneau [1984], Haslinger and Neittaanmaki [1988], [1996], Sokolowski...  Read More >>

The calculus of variations has a long history of interaction with other branches of mathematics such as geometry...  Read More >>

In the early fifties, applied mathematicians, engineers and economists started to pay c10se attention to the optimization...  Read More >>

Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising...  Read More >>

Since I started working in the area of nonlinear programming and, later on, variational inequality problems, I have...  Read More >>