An informal analysis is provided for the basic concepts associated with multi-objective optimization and the notion of Pareto-optimality, particularly in the context of genetic algorithms. A number of evolutionary algorithms developed for this purpose are also briefly introduced, and finally, a number of paradigm examples are presented from the materials and manufacturing sectors, where multi-objective genetic algorithms have been successfully utilized in the recent past.
Key Terms in this Chapter
Magneto-Rheological Fluid: A smart material for engineering applications. Its physical and mechanical properties can be tailor-made by adjusting a magnetic field.
Non-Calculus-Type Algorithms: The optimization algorithms that do not require any derivatives or gradient information. Commonly used to describe genetic and evolutionary algorithms.
Yankee: A device used in the paper mills which essentially is a very large heated cylinder with a highly polished surface.
Classical Techniques: Multi-objective optimization routines that are not evolutionary in nature. Most are based upon rigid mathematical principles and are commonly gradient based.
Superalloy: A specially designed category of multi-component alloys used in advanced engineering applications.
Crown: A quantifier for the surface flatness of the rolled metal sheets.
Guillotine Cutting: Edge-to-edge cutting of materials, most commonly metals.
Pareto-Optimality: The concept of the family of optimized solutions for a multi-objective problem proposed by Vilfredo Pareto (1848-1923 AU17: The in-text citation "Vilfredo Pareto (1848-1923" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ).
Continuous Stirred Tank Reactor (CSTR): A specially designed agitated vessel used for carrying out chemical reactions.
William and Otto Chemical Plant: A hypothetical chemical plant used as a common test problem in chemical engineering literature.
Complete Chapter List
P. Collet, J. Rennard
I. Naveh, R. Sun
J. Barr, F. Saraceno
H. Kwasnicka, W. Kwasnicki
A. Berro, I. leroux
N. J. Saam, W. Kerber
A. Brabazon, A. Silva, T. F.S. Sousa, R. Matthews, M. O’Neill
G. D.M. Serugendo
K. Taveter, G. Wagner
L. Shan, R. Shen, J. Wang
M. Klein, P. Faratin, H. Sayama
A. Mochon, Y. Saez
R. Marks, D. Midgley, L. Cooper
T. Erez, S. Moldovan, Soloman
M. Ciprian, M. Kaucic
S. Lavigne, S. Sanchez