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Brunet, M, Motamedi, A, Guénette, L and Forgues, D (2019) Analysis of BIM use for asset management in three public organizations in Québec, Canada. Built Environment Project and Asset Management, 9(01), 153–67.

Che Ibrahim, C K I, Mohamad Sabri, N A, Belayutham, S and Mahamadu, A (2019) Exploring behavioural factors for information sharing in BIM projects in the Malaysian construction industry. Built Environment Project and Asset Management, 9(01), 15–28.

Duryan, M and Smyth, H (2019) Service design and knowledge management in the construction supply chain for an infrastructure programme. Built Environment Project and Asset Management, 9(01), 118–37.

Fuentes, M E (2019) Co-creation and co-destruction of experiential value: a service perspective in projects. Built Environment Project and Asset Management, 9(01), 100–17.

Hassanain, M A, Aljuhani, M, Sanni-Anibire, M O and Abdallah, A (2019) Interdisciplinary design checklists for mechanical, electrical and plumbing coordination in building projects. Built Environment Project and Asset Management, 9(01), 29–43.

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, 9(01), 44–63.

• Type: Journal Article
• Keywords: Multi-objective optimization; Global optimization; Construction quality assessment system (CONQUAS); Multi-criterion decision-making; Multi-mode resource-constrained project scheduling; Time–cost–quality;
• ISBN/ISSN: 2044-124X
• URL: https://doi.org/10.1108/BEPAM-04-2018-0075
• Abstract:
  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.

Lim, T, Porras-Alvarado, J D and Zhang, Z (2019) Pricing of highway infrastructure for transportation asset management. Built Environment Project and Asset Management, 9(01), 64–79.

Murphy, M and Eadie, R (2019) Socially responsible procurement. Built Environment Project and Asset Management, 9(01), 138–52.

Smyth, H, Duryan, M and Kusuma, I (2019) Service design for marketing in construction. Built Environment Project and Asset Management, 9(01), 87–99.

Zhou, H and Rezazadeh Azar, E (2019) BIM-based energy consumption assessment of the on-site construction of building structural systems. Built Environment Project and Asset Management, 9(01), 2–14.