Strategies for multiobjective genetic algorithm development: Application to optimal batch plant design in process systems engineering

Strategies for multiobjective genetic algorithm development: Application to optimal batch plant design in process systems engineering

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Article ID: iaor2009887
Country: Netherlands
Volume: 54
Issue: 3
Start Page Number: 539
End Page Number: 569
Publication Date: Apr 2008
Journal: Computers & Industrial Engineering
Authors: , , ,
Keywords: planning, heuristics: genetic algorithms
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 are described in detail. Several performance tests are presented, based on the influence of bit ranging encoding in a chromosome.

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