Probabilistic Sustainable Design Using Multiobjective Optimization Model

Project managers (PMs) are currently charged with achieving a balance between cost and duration, and must consider environmental factors to reach sustainable development. This work proposes a novel probabilistic multi-objective optimization algorithm to attain sustainable construction cost, project duration, and CO2 emissions simultaneously in an uncertain project environment. The algorithm, based on particle swarm optimization integrated with Monte Carlo simulation, is applied to generate a low-carbon economy and cleaner production. A typical construction project is selected to demonstrate the application for making sustainable decisions with a set of non-dominant design solutions under multi-objective optimization.