4.7 Article

Integrated scheduling of suppliers and multi-project activities for green construction supply chains under uncertainty

Journal

AUTOMATION IN CONSTRUCTION
Volume 122, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.autcon.2020.103485

Keywords

Construction project; Green supply chain; Supplier selection; Project scheduling; Scenario fuzzy number

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The study evaluates the green construction supply chain using a mathematical model while considering environmental impacts and uncertain factors. The paper also discusses the synergy between supplier selection and project planning, as well as operational challenges in the construction industry.
The green construction supply chain is one of the topics that have been recently discussed in relation to supply chain fundamentals, especially in the construction supply chain. Specifically, a project network consisting of several concurrent projects is managed with the aim of not only minimizing delays in all projects, but also simultaneously minimizing the logistical costs, e.g., procurement, ordering, and transportation costs, and pollution levels of vehicles. Although these projects operate independently, they are affected by common suppliers and final quality inspection by the common committee, thus requiring consistent project review. This study evaluates the construction supply chain using a mathematical model of bi-objective linear programming. To realize this objective, the actual environmental impacts of vehicles in terms of distance, pollution rate, and slope of the road are considered. This paper also discusses the synergy between supplier selection and project planning and scheduling in the proposed green supply chain. In addition, the issues of balancing the supplier selection, choosing the type of fleet, and project time planning, which has become a real operational challenge in the construction industry, are also investigated in the paper such that by minimizing the project delays, logistical costs and the propagation of greenhouse gases can be minimized as well. Moreover, in order to make the results more realistic, the levels of production capacity and costs are considered in an uncertain (fuzzy-probabilistic) environment under three economic conditions, i.e., pessimistic, normal, and optimistic.

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