Approximation Optimization Computing

Approximation, Optimization, and Computing

This volume consists of 101 papers in the areas of approximation, optimization and computing, and applications. Under the sponsorship of IMACS (The International Association for Mathematics and Computers in Simulation), it represents a collaborative venture, initiated in 1986, between the Dalian University of Technology and the University of Regina. A primary goal of the project was to encourage research papers reflecting emerging directions within theory and applications. Covered are the following: analytic or discrete approximations, optimization applications, deterministic or stochastic processes, programming, and applications of theory or techniques in engineering or other sciences.

Approximation, Optimization & Computing

Algorithmics for Hard Problems

Algorithmic design, especially for hard problems, is more essential for success in solving them than any standard improvement of current computer technologies. Because of this, the design of algorithms for solving hard problems is the core of current algorithmic research from the theoretical point of view as weIl as from the practical point of view. There are many general textbooks on algorithmics, and several specialized books devoted to particular approaches such as local search, randomization, approximation algorithms, or heuristics. But there is no textbook that focuses on the design of algorithms for hard computing tasks, and that systematically explains, combines, and compares the main possibilities for attacking hard algorithmic problems. As this topic is fundamental for computer science, this book tries to elose this gap. Another motivation, and probably the main reason for writing this book, is connected to education. The considered area has developed very dynamically in recent years and the research on this topic discovered several profound re sults, new concepts, and new methods. Some of the achieved contributions are so fundamental that one can speak about paradigms which should be ineluded in the education of every computer science student. Unfortunately, this is very far from reality. This is because these paradigms are not sufficiently known in the computer science community, and so they are insufficiently communicated to students and practitioners.