Neural network embedded multiobjective genetic algorithm to solve non-linear time-cost tradeoff problems of project scheduling

Abstract

This paper presents a novel method to solve non-linear time-cost tradeoff (TCT) problem of real world engineering projects. Multiobjective genetic algorithm (MOGA) is employed to search for optimal TCT profile. Applicability of ANN based model for rapid estimation of time-cost relationship by invoking its function approximation capability is investigated. ANN models are then integrated with MOGA so as to develop a comprehensive approach to solve non-linear TCT problems of project scheduling. The study has implications in real time monitoring and control of project scheduling process.