Scholarlink

<p>This study presents a Comprehensive Adaptive Penalty Scheme integrated with the Non-Dominated Sorting Genetic Algorithm III (CAPS–NSGA-III) for multi-objective optimization of construction scheduling in high-rise residential projects executed using Mivan aluminum formwork technology. Moving beyond conventional time–cost trade-off models, the proposed framework simultaneously minimizes five conflicting objectives: total project duration, construction cost, defect index (quality), accident risk (safety), and carbon dioxide (CO₂) emissions (environmental impact). The scheduling problem is formulated as a multi-mode activity model with strict precedence, mode exclusivity, and feasibility constraints. To enhance convergence and feasibility preservation, a dynamic adaptive penalty mechanism is employed that adjusts constraint severity based on generation progress and population feasibility ratio. The framework is validated using a real G + 15 residential project in Meerut, India, consisting of 21 activities with three execution modes (Normal, Fast-Track, and Eco-Friendly). Results demonstrate that the proposed CAPS–NSGA-III significantly outperforms the standard NSGA-III, achieving a feasibility ratio of 98.2%, improved hypervolume (0.885), and faster convergence. Seventeen feasible Pareto-optimal schedules were generated, revealing explicit trade-offs among sustainability, safety, quality, and economic performance. A post-optimization decision-support process integrating Analytic Hierarchy Process-based weights with the Technique for Order Preference by Similarity to Ideal Solution identified an eco-balanced schedule that reduced carbon emissions (123.76 t) and accident risk (0.21%) with only marginal schedule extension. The proposed framework demonstrates strong scalability, robustness, and practical applicability for sustainable and safety-oriented planning of high-rise construction projects.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Comprehensive adaptive penalty-based non-dominated sorting genetic algorithm III for multi-objective trade-off optimization of construction scheduling using mivan formwork technology in high-rise buildings

  • 期刊论文

  • 发表日期：

    2026年4月9日

查看全文
  • Atole Tanaji Vaman,
  • Manoj Sharma

摘要

This study presents a Comprehensive Adaptive Penalty Scheme integrated with the Non-Dominated Sorting Genetic Algorithm III (CAPS–NSGA-III) for multi-objective optimization of construction scheduling in high-rise residential projects executed using Mivan aluminum formwork technology. Moving beyond conventional time–cost trade-off models, the proposed framework simultaneously minimizes five conflicting objectives: total project duration, construction cost, defect index (quality), accident risk (safety), and carbon dioxide (CO₂) emissions (environmental impact). The scheduling problem is formulated as a multi-mode activity model with strict precedence, mode exclusivity, and feasibility constraints. To enhance convergence and feasibility preservation, a dynamic adaptive penalty mechanism is employed that adjusts constraint severity based on generation progress and population feasibility ratio. The framework is validated using a real G + 15 residential project in Meerut, India, consisting of 21 activities with three execution modes (Normal, Fast-Track, and Eco-Friendly). Results demonstrate that the proposed CAPS–NSGA-III significantly outperforms the standard NSGA-III, achieving a feasibility ratio of 98.2%, improved hypervolume (0.885), and faster convergence. Seventeen feasible Pareto-optimal schedules were generated, revealing explicit trade-offs among sustainability, safety, quality, and economic performance. A post-optimization decision-support process integrating Analytic Hierarchy Process-based weights with the Technique for Order Preference by Similarity to Ideal Solution identified an eco-balanced schedule that reduced carbon emissions (123.76 t) and accident risk (0.21%) with only marginal schedule extension. The proposed framework demonstrates strong scalability, robustness, and practical applicability for sustainable and safety-oriented planning of high-rise construction projects.