The purpose of this paper is to develop a framework to optimize time, cost and quality in a multi-mode resource-constrained project scheduling environment.
A case study approach identified the activity execution modes in building construction projects in India to support multi-mode resource-constrained project scheduling. The data required to compute time, cost and quality of each activity are compiled from real construction projects. A binary integer-programming model has been developed to perform multi-objective optimization and identify Pareto optimal solutions. The RR-PARETO3 algorithm was used to identify the best compromise trade-off solutions. The effectiveness of the proposed framework is demonstrated through sample case study projects.
Results show that good compromise solutions are obtained through multi-objective optimization of time, cost and quality.
Case study data sets were collected only from eight building construction projects in India.
It is feasible to adopt multi-objective optimization in practical construction projects using time, cost and quality as the objectives; Pareto surfaces help to quantify relationships among time, cost and quality. It is shown that cost can be reduced by increasing the duration, and quality can be improved only by increasing the cost.
The use of different activity execution modes compiled from multiple projects in optimization is illustrated, and good compromise solutions for the multi-mode resource-constrained project scheduling problems using multi-objective optimization are identified.
The doctoral research study of the first author was supported by the Ministry of Human Resource Development (MHRD), India, and scholarship from Swinburne University Postgraduate Research Award (SUPRA), Australia. The authors would like to thank reviewers for their invaluable comments.
Kannimuthu, M., Raphael, B., Palaneeswaran, E. and Kuppuswamy, A. (2019), "Optimizing time, cost and quality in multi-mode resource-constrained project scheduling", Built Environment Project and Asset Management, Vol. 9 No. 1, pp. 44-63. https://doi.org/10.1108/BEPAM-04-2018-0075
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