The Williams and Otto Chemical Plant re-evaluated using a Pareto-optimal formulation aided by Genetic Algorithms

Authors:
N. Chakraborti;P. Mishra;A. Aggarwal;A. Banerjee;S. S. Mukherjee
Affiliations:
Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur 721302, India;Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur 721302, India;Department of Metallurgical Engineering, Regional Engineering College, Trichy, India;Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur 721302, India;Department of Metallurgical and Materials Engineering, Indian Institute of Technology, Kharagpur 721302, India
Venue:
Applied Soft Computing
Year:
2006

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Abstract

The Williams and Otto Chemical Plant is a classic example of a complex nonlinear programming problem incorporating the essential features of a chemical or hydrometallurgical processing plant. An efficient solution strategy for this time tested problem is shown here which uses different variants of biologically inspired Genetic Algorithms and is aided by a multi-objective formulation. The Genetic Algorithms worked more efficiently than the classical techniques used earlier and the nature of the feasible solutions was clearly revealed by the Pareto-optimality concept embedded in the multi-objective optimization employed here.