Scholarlink

<p>This study proposes an improved Jaya-based multi-objective optimization framework for large-scale construction projects, simultaneously addressing time, cost, quality, and safety performance. The model integrates these four interdependent dimensions into a unified decision-making structure and is evaluated using both benchmark test functions and a real civil construction case study. Comparative analyses against the original Jaya algorithm, Particle Swarm Optimization, and the Bat Algorithm demonstrate that the improved Jaya variant consistently achieves superior convergence and more balanced optimization across all objectives. The results highlight the algorithm’s enhanced ability to escape local optima and provide robust trade-off solutions, confirming its effectiveness as a practical tool for time–cost–quality–safety optimization in complex construction environments.</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

An improved Jaya-based multi-objective optimization framework for time–cost–quality–safety trade-offs in large-scale construction

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月16日

查看全文
  • Seyed Ali Miri,
  • Ameneh Farahani

摘要

This study proposes an improved Jaya-based multi-objective optimization framework for large-scale construction projects, simultaneously addressing time, cost, quality, and safety performance. The model integrates these four interdependent dimensions into a unified decision-making structure and is evaluated using both benchmark test functions and a real civil construction case study. Comparative analyses against the original Jaya algorithm, Particle Swarm Optimization, and the Bat Algorithm demonstrate that the improved Jaya variant consistently achieves superior convergence and more balanced optimization across all objectives. The results highlight the algorithm’s enhanced ability to escape local optima and provide robust trade-off solutions, confirming its effectiveness as a practical tool for time–cost–quality–safety optimization in complex construction environments.