Abstract
This paper proposes an approach for strategic revenue management under uncertainty for real estate projects. It integrates three modelling techniques: first, artificial neural network integrated support vector machines for forecasting the profit and loss-making real estate residential projects; second, analytical network process approach using decision making trials and evaluation laboratory methodology for establishing interrelationships among factors; and third, multiobjective genetic algorithm approach for obtaining optimal numbers and types of apartments in a real estate project. We compare the respective revenues generated with the new number of apartments and price from the suggested revenue maximization model and that of the old practiced one through a case study of India. Copyright © 2015 John Wiley & Sons, Ltd.
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