Genetic Algorithms and Engineering Optimization

ISBN-13: 9780471315315 / Angielski / Twarda / 1999 / 512 str.

Runwei Cheng; Mitsuo Gen;Gen

Opis

This text addresses one of the most important optimization techniques in the industrial engineering manufacturing areas; the use of genetic algorithms to improve design and produce reliable products of high quality. Genetic algorithms is a probabilistic search technique which is based on the principles of biological evolution. As biological entities continually evolve and adapt genetically towards an individual which is more suitable to its environment so a genetic algorithm will follow paths of analysis which evolve a specific design towards the best result based on the environmental constraints expected to be placed upon it.

Spis treści

Foundations of Genetic Algorithms.

Combinatorial Optimization Problems.

Multiobjective Optimization Problems.

Fuzzy Optimization Problems.

Reliability Design Problems.

Scheduling Problems.

Advanced Transportation Problems.

Network Design and Routing.

Manufacturing Cell Design.

References.

Index.

O autorze

MITSUO GEN, PhD, is a professor in the Department of Industrial and Information Systems Engineering at the Ashikaga Institute of Technology in Ashikaga, Japan.

RUNWEI CHENG, PhD, is an associate professor in the Institute of Systems Engineering at Northeastern University in Shenyang, China.

Blurb

A comprehensive guide to a powerful new analytical tool by two of its foremost innovators

The past decade has witnessed many exciting advances in the use of genetic algorithms (GAs) to solve optimization problems in everything from product design to scheduling and client/server networking. Aided by GAs, analysts and designers now routinely evolve solutions to complex combinatorial and multiobjective optimization problems with an ease and rapidity unthinkable withconventional methods. Despite the continued growth and refinement of this powerful analytical tool, there continues to be a lack of up–to–date guides to contemporary GA optimization principles and practices. Written by two of the world′s leading experts in the field, this book fills that gap in the literature.

Taking an intuitive approach, Mitsuo Gen and Runwei Cheng employ numerous illustrations and real–world examples to help readers gain a thorough understanding of basic GA concepts–including encoding, adaptation, and genetic optimizations–and to show how GAs can be used to solve an array of constrained, combinatorial, multiobjective, and fuzzy optimization problems. Focusing on problems commonly encountered in industry–especially in manufacturing–Professors Gen and Cheng provide in–depth coverage of advanced GA techniques for:
∗ Reliability design
∗ Manufacturing cell design
∗ Scheduling
∗ Advanced transportation problems
∗ Network design and routing

Genetic Algorithms and Engineering Optimization is an indispensable working resource for industrial engineers and designers, as well as systems analysts, operations researchers, and management scientists working in manufacturing and related industries. It also makes an excellent primary or supplementary text for advanced courses in industrial engineering, management science, operations research, computer science, and artificial intelligence.