Title
Strategies for multiobjective genetic algorithm development: Application to optimal batch plant design in process systems engineering
Abstract
This work deals with multiobjective optimization problems using Genetic Algorithms (GA). A MultiObjective GA (MOGA) is proposed to solve multiobjective problems combining both continuous and discrete variables. This kind of problem is commonly found in chemical engineering since process design and operability involve structural and decisional choices as well as the determination of operating conditions. In this paper, a design of a basic MOGA which copes successfully with a range of typical chemical engineering optimization problems is considered and the key points of its architecture described in detail. Several performance tests are presented, based on the influence of bit ranging encoding in a chromosome. Four mathematical functions were used as a test bench. The MOGA was able to find the optimal solution for each objective function, as well as an important number of Pareto optimal solutions. Then, the results of two multiobjective case studies in batch plant design and retrofit were presented, showing the flexibility and adaptability of the MOGA to deal with various engineering problems.
Year
DOI
Venue
2008
10.1016/j.cie.2007.09.007
Computers & Industrial Engineering
Keywords
DocType
Volume
multiobjective genetic algorithm,chemical engineering,process design,basic moga,multiobjective case study,multiobjective optimization,various engineering problem,batch plant design,pareto sort procedure,typical chemical engineering optimization,multiobjective ga,multiobjective problem,process systems engineering,multiobjective optimization problem,multiobjective genetic algorithm development,optimization problem,objective function,operant conditioning,genetic algorithm
Journal
54
Issue
ISSN
Citations 
3
Computers & Industrial Engineering
3
PageRank 
References 
Authors
0.42
20
4
Name
Order
Citations
PageRank
A. Dietz1203.02
C. Azzaro-Pantel2346.37
L. Pibouleau3366.79
S. Domenech450.84