Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems.
Customer-Oriented Optimization in Public Transportation develops models, results and algorithms for optimizing public transportation from a customer-oriented point of view.
In this global society, manufacturers compete in many ways, and information infrastructures play a critical role in ensuring the right information is available at the right time and the right place to support informed decision making.
In the field of nondifferentiable nonconvex optimization, one of the most intensely investigated areas is that of optimization problems involving multivalued mappings in constraints or as the objective function.
Complementarity theory, a relatively new domain in applied mathematics, has deep connections with several aspects of fundamental mathematics and also has many applications in optimization, economics and engineering.
Linear programming attracted the interest of mathematicians during and after World War II when the first computers were constructed and methods for solving large linear programming problems were sought in connection with specific practical problems-for example, providing logistical support for the U.
Although transportation economists have advocated the tolling of urban streets as a mechanism for controlling congestion and managing travel demands for over 50 years, it is only recently that this idea has become practical.
Large-Scale Nonlinear Optimization reviews and discusses recent advances in the development of methods and algorithms for nonlinear optimization and its applications, focusing on the large-dimensional case, the current forefront of much research.
Most books about global optimization describe the theory of the algorithms, whereas a given implementation's quality never depends exclusively on the theoretical soundness of the algorithms that are implemented.
Robust design-that is, managing design uncertainties such as model uncertainty or parametric uncertainty-is the often unpleasant issue crucial in much multidisciplinary optimal design work.
Search Methodologies is a tutorial survey of the methodologies that are at the confluence of several fields: Computer Science, Mathematics and Operations Research.
Over the last twenty years, Professor Franco Giannessi, a highly respected researcher, has been working on an approach to optimization theory based on image space analysis.
Continuous optimization is the study of problems in which we wish to opti- mize (either maximize or minimize) a continuous function (usually of several variables) often subject to a collection of restrictions on these variables.
During the last decade I have explored the consequences of what I have chosen to call the 'consistent preferences' approach to deductive reasoning in games.
Metaheuristics: Progress as Real Problem Solvers is a peer-reviewed volume of eighteen current, cutting-edge papers by leading researchers in the field.
