A Review of Energy-Efficient and Sustainable Construction Scheduling Supported with Optimization Tools

Abstract

This article reviews the accomplishments of studies in which optimization tools were used to develop energy-efficient and sustainable construction schedules. With the increase in global awareness of environmental issues, the construction industry has been forced to explore innovative techniques to make the building process more energy-efficient and sustainable. Project managers can use optimization tools in their scheduling procedures to address these issues in the early stages of the project. Therefore, this paper examines different optimization-based construction scheduling methods and their impact on schedule energy efficiency and the three key sustainability goals: economic viability, social equity, and environmental protection. Such a review has not yet been conducted to the best of our knowledge. This research aims to fill the gap and contribute to understanding advanced optimization tools that can pave the way to energy-efficient and sustainable scheduling practices. After a brief introduction, the background of optimization-based construction scheduling techniques that aim to improve construction management and incorporate these aspects into the decision-making process is explained. Then, these approaches are addressed in detail. It is determined for each study whether it adopted energy efficiency goals and which sustainability dimensions it considered within the proposed optimization model. The results of this study indicate a wide heuristic algorithms application for complex scheduling problems. Meanwhile, mathematical programming is still quite unexplored, especially methods that utilize algebraic modeling languages. This study provides a foundation for further research by addressing the current reach in development and possible knowledge gaps that could be researched in future studies. The paper also discusses the advantages and limitations of different approaches and illustrates the potential for utilizing these methods. Supported by the main review findings, conclusions and recommendations for further research are provided.