ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Pareto-optimal solutions for multi-objective optimization of fed-batch bioreactors using nondominated sorting genetic algorithm.

Sarkar, Debasis and Modak, Jayant M (2004) Pareto-optimal solutions for multi-objective optimization of fed-batch bioreactors using nondominated sorting genetic algorithm. In: Chemical Engineering Science., 60 (2). pp. 481-492.

[img] PDF
Pareto-optimal_-pdf.sl.no.62.pdf
Restricted to Registered users only

Download (390Kb) | Request a copy

Abstract

Many optimal control problems are characterized by their multiple performance measures that are often noncommensurable and competing with each other. The presence of multiple objectives in a problem usually give rise to a set of optimal solutions, largely known as Pareto-optimal solutions. Evolutionary algorithms have been recognized to be well suited for multi-objective optimization because of their capability to evolve a set of nondominated solutions distributed along the Pareto front. This has led to the development of many evolutionary multi-objective optimization algorithms among which Nondominated Sorting Genetic Algorithm (NSGA and its enhanced version NSGA-II) has been found effective in solving a wide variety of problems. Recently, we reported a genetic algorithm based technique for solving dynamic single-objective optimization problems, with single as well as multiple control variables, that appear in fed-batch bioreactor applications. The purpose of this study is to extend this methodology for solution of multi-objective optimal control problems under the framework of NSGA-II. The applicability of the technique is illustrated by solving two optimal control problems, taken from literature, which have usually been solved by several methods as single-objective dynamic optimization problems.

Item Type: Journal Article
Additional Information: The copyright of this article belongs to Elsevier.
Keywords: Fed-batch;Bioreactors;Fermentation;Systems engineering;Nondominated sorting genetic algorithm;Optimization
Department/Centre: Division of Mechanical Sciences > Chemical Engineering
Date Deposited: 09 Mar 2006
Last Modified: 19 Sep 2010 04:24
URI: http://eprints.iisc.ernet.in/id/eprint/5874

Actions (login required)

View Item View Item