Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/758
Title: Neural network embedded multiobjective genetic algorithm to solve non-linear time-cost tradeoff problems of project scheduling
Authors: Pathak, Bhupendra Kumar
Srivastava, Sanjay
Srivastava, Kamal
Keywords: Artificial neural network
Multiobjective genetic algorithm
Project scheduling
Time-cost tradeoff (TCT)
Issue Date: Feb-2008
Publisher: CSIR
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.
Description: 124-131
URI: http://hdl.handle.net/123456789/758
ISSN: 0022-4456
Appears in Collections:JSIR Vol.67(02) [February 2008]

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