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.