Thursday, June 18, 2015

Engineering Optimization - Courses and Resources

Engineering Optimization - Journal - Current Issue


Source:  - downloaded on 17 June 2015

Northwestern Engineering Course

NPTEL Course

Kelvin's Law of Economic Size of Conductor (Engineering Economics by Taylor)

Optimization of Helical Spring - Gear - 2002 MS Thesis

University of Maryland Course


Seco Tools India article on metal cutting optimization

2012 Paper
On the Economics of Computer Assisted Numerically Controlled Cylindrical Turning Operations - Optimized Conditions for Maximum Rate of Profit.- - T.K. Jack and O.M.U. Etubu

A review of optimization techniques in metal cutting processes
Indrajit Mukherjee , Pradip Kumar Ray,
a Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur 721 302, India
Computers & Industrial Engineering
Volume 50, Issues 1–2, May 2006, Pages 15–34


Cutting Speed and Feed Rate Optimization for Minimizing
Production Time of Turning Process
S. S. K. Deepak
(Department of Mechanical Engineering, Rungta Engineering College, Raipur, Chhattisgarh, India)
International Journal of Modern Engineering Research (IJMER)
Vol.2, Issue.5, Sep-Oct. 2012 pp-3398-3401


Multi-objective optimization of industrial hydrogen plants
J. K. Rajesh!, S. K. Gupta",1, G. P. Rangaiah!, A. K. Ray!,*
!Department of Chemical and Environmental Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore
"Department of Chemical Engineering, University of Wisconsin, Madison, WI 53706, USA
Chemical Engineering Science 56 (2001) 999-1010

Genetic Algorithms and Engineering Optimization
Mitsuo Gen, Runwei Cheng

John Wiley & Sons, 2000 - Computers - 495 pages
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.
Google book link with preview facility

Updated  18 June, 23 May 2015
First publisedh  29 6 2013

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