What does this research mean for the field?

Integrating EnergyPlus simulation with a Particle Swarm Optimization algorithm provides a multi-objective framework that simultaneously reduces primary energy consumption, thermal discomfort, and life cycle costs in industrial building retrofits. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To establish a multi-objective optimization framework that simultaneously minimizes primary energy consumption, life cycle costs, and thermal discomfort in industrial buildings.

September 14, 2026International Journal of Construction ManagementOpen Access

A multi-objective energy retrofit optimization framework for enhancing sustainability in industrial buildings

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Authors

ASAmir Safari MTMehdi Tavakolan FMFarzad Mostafazadeh

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Overview

Computational optimization study demonstrates substantial reductions in energy use, costs, and thermal discomfort in an industrial building, highlighting scalable retrofit strategies.

Key Points

To establish a multi-objective optimization framework that simultaneously minimizes primary energy consumption, life cycle costs, and thermal discomfort in industrial buildings.
Integrated EnergyPlus building energy simulation with a MATLAB-based Particle Swarm Optimization (PSO) algorithm.
Modeled building envelope upgrades, HVAC efficiency improvements, maintenance strategies, and operational schedule modifications on an operational stone processing plant.
Assessed trade-offs and interdependencies among key sustainability metrics using Pearson and Spearman correlation analyses.
Achieved maximum annual primary energy savings of up to 85,855 kWh (approximately 39 kWh/m²) alongside a life cycle cost reduction of up to 9% over a 20-year horizon.
Decreased thermal discomfort hours from a baseline of 51% to 15% under optimal comfort-oriented configurations, representing a 36 percentage-point absolute reduction (approximately a 71% relative reduction).

Cite This Study

Safari et al. (2026) studied this question.

synapsesocial.com/papers/6aa7b3fc0926e14a848b3647 https://doi.org/10.1080/15623599.2026.2731425

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September 14, 2026International Journal of Construction ManagementOpen Access

A multi-objective energy retrofit optimization framework for enhancing sustainability in industrial buildings

View Full Paper

Ask AI

Bookmark

Authors

ASAmir Safari MTMehdi Tavakolan FMFarzad Mostafazadeh

Discussion

Member takes

Overview

Computational optimization study demonstrates substantial reductions in energy use, costs, and thermal discomfort in an industrial building, highlighting scalable retrofit strategies.

Key Points

To establish a multi-objective optimization framework that simultaneously minimizes primary energy consumption, life cycle costs, and thermal discomfort in industrial buildings.
Integrated EnergyPlus building energy simulation with a MATLAB-based Particle Swarm Optimization (PSO) algorithm.
Modeled building envelope upgrades, HVAC efficiency improvements, maintenance strategies, and operational schedule modifications on an operational stone processing plant.
Assessed trade-offs and interdependencies among key sustainability metrics using Pearson and Spearman correlation analyses.
Achieved maximum annual primary energy savings of up to 85,855 kWh (approximately 39 kWh/m²) alongside a life cycle cost reduction of up to 9% over a 20-year horizon.
Decreased thermal discomfort hours from a baseline of 51% to 15% under optimal comfort-oriented configurations, representing a 36 percentage-point absolute reduction (approximately a 71% relative reduction).

Cite This Study

Safari et al. (2026) studied this question.

synapsesocial.com/papers/6aa7b3fc0926e14a848b3647 https://doi.org/10.1080/15623599.2026.2731425

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