https://orcid.org/0000-0002-3556-3802
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ABSTRACT
This study addresses the challenges of designing sustainable structures that minimize energy consumption and costs. It introduces a novel optimization algorithm, the Developed Multi-Verse Optimization Algorithm (DMVO), to overcome the limitations of existing simulation software. The DMVO algorithm optimizes structure envelope parameters, such as walls, windows, and glass curtain walls, to achieve lower energy consumption and construction costs. It outperforms other methods, such as EHO, SAR, LSO, and MVO, in terms of energy efficiency and cost-effectiveness. Moreover, it converges to the optimal solution in fewer iterations, reaching the best result in the 65th iteration. It obtains the minimum values of and
as 12,397,493.7 RMB and 48.7673 kWh/m2y, respectively. The proposed algorithm enhances natural ventilation and internal lighting by increasing the glass curtain wall and window areas. It demonstrates its superior performance in saving energy in structures compared to other methods, achieving approximately a 38% reduction in total costs compared to the initial design. This research provides a promising method that can be generalized to various structure types and climates in future projects, contributing to the advancement of sustainable construction practices. Overall, the DMVO algorithm is a significant contribution to the field of sustainable structure design, offering an effective approach to improve energy efficiency and cost-effectiveness while reducing environmental impact.
Abbreviations
| Abbreviation | = | Definition |
| DMVO | = | Developed Multiverse Optimization |
| MOPSO | = | Multi-Objective Particle Swarm Optimization |
| NSGA-II | = | Genetic method II |
| SA | = | Simulated Annealing |
| BEO | = | Building Energy Optimization |
| MOGA | = | Multi-Objective Genetic Algorithm |
| PSO | = | particle swarm optimization |
| CAD | = | Computer-Aided Design |
| MVO | = | Multi-Verse Optimization MVO |
| WEP | = | Wormhole Existence Probability |
| TDR | = | Traveling Distance Rate |
| LSO | = | Locust Swarm Optimization |
| SAR | = | Search and Rescue Optimization Algorithm |
| EHO | = | Elephant Herding Optimization |
| HVAC | = | Heating, Ventilation, and Air Conditioning |
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Yunjie Wan
Yunjie Wan was born in Guangdong, China, in 1998. From 2017 to 2021, he studied in Oregon State University and received his bachelor’s degree in 2021. From 2021 to 2023, he studied in University of Sydney and received his Master’s degree in 2023. Currently, he works in Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment of the People’s Republic of China. He has published zero papers. His research interests are included safe disposal of solid waste and resource utilization.
Yimeng Ju
Yimeng Ju was born in Henan. China, in 1994. From 2012 to 2016, she studied in Xinjiang University and received her bachelor’s degree in Environmental Science. From 2017 to 2021, she worked in Henan Water Conservancy and Hydropower School. From 2017, she studied in Oregon State Univiersity and she recevied her Master’s degree in Environmental Science in 2020. Currently, she works in Henan First Geological Brigade Co., Ltd. Her research interests are included Environmental Science.
Sama Abdolhosseinzadeh
Sama Abdolhosseinzadeh received a Master’s degree in Engineering from the University of Mohaghegh Ardabili, Ardabil, Iran in 2020. His research interests are applying artificial intelligence and heuristic optimization methods to power system control design, operation and planning, and power system restructuring. He has authored and co-authored 4 books in the Engineering area all in Farsi, one book and 2 book chapters in international publishers, and more than 10 papers in international journals and conference proceedings. Also, he collaborates with several international journals as a reviewer board and works on an editorial committee of three international journals.