Optimizing cost and CO2 emission for construction projects using particle swarm optimization

Under an intensive competitive environment, the construction industry is facing pressure to meet the higher customer expectations under a tighter budget. On the other hand, construction is one of the main sectors generating greenhouse gases. The aim of this study is to assist decision-makers to identify the trade-off solution between construction cost and CO2 emission. A particle swarm optimization model is proposed. First, construction projects are broken down into a series of work packages or subsections and all the resource options for each work subsection are then defined. Second, the total CO2 emissions, both direct and indirect, resulting from each resource option are estimated. Third, the total construction costs, comprising material cost plus any additional fee for each resource option are calculated. Fourth, particle swarm optimization is employed to search for the Pareto-optimal solutions, and derives a set of combinations of resource options for each work subsection. Lastly, decision-makers can select the final trade-off solution from such a set of optimal solutions based on their preference. A genuine construction renovation project is used to evaluate the workability of the proposed model and the results fully demonstrate its validity and practicality.

► Reducing CO2 emissions will increase construction costs.
► We apply PSO to identify trade-off solutions between costs and CO2 emissions.
► A genuine project is used to evaluate the workability of the proposed model.
► The proposed model has good performance in both costs and CO2 reductions.