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An improved multi-objective animated oat optimization algorithm for resource-constrained construction project

Qing Xue1, Chunjiang Wu2, Jiyang Nie1

  • 1School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China.

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Summary
This summary is machine-generated.

This study introduces the Multi-Objective Animated Oat Optimization (MOAOO) algorithm to improve construction project organization design. MOAOO enhances resource allocation, balances conflicting objectives like cost and duration, and demonstrates practical value in engineering management.

Keywords:
Constrained project schedulingCost tradeMetaheuristic algorithmOffProject managementResourceTime

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Area of Science:

  • Engineering Management
  • Computational Intelligence
  • Optimization Algorithms

Background:

  • Global urbanization drives large-scale construction projects, necessitating optimized organization design.
  • Conventional methods face challenges in resource efficiency, multi-objective conflict resolution, and dynamic adjustments.
  • Existing optimization techniques are insufficient for complex construction project organization design.

Purpose of the Study:

  • To develop the first multi-objective extension of the Animated Oat Optimization algorithm (MOAOO) for construction project organization design.
  • To address limitations of empirical decision-making in resource allocation and multi-objective conflict management.
  • To introduce a novel optimization approach for enhanced dynamic adjustment capabilities.

Main Methods:

  • Developed MOAOO by extending the biological mechanism of Animated Oat Optimization.
  • Incorporated a hybrid position update rule with Elite Reference Points and stochastic perturbations.
  • Implemented a three-layer constraint processing mechanism and a dual-threshold convergence monitoring system.
  • Integrated dynamic elite retention, non-dominated sorting, and dynamic archive mechanisms for collaborative optimization.

Main Results:

  • MOAOO demonstrated competitive performance against advanced algorithms (Pre-DEMO, MOEA/D-OED, Pi-MOEA) on ZDT test functions.
  • Achieved significant reduction in resource fluctuation (72.7%) in a case study.
  • Successfully balanced conflicting objectives: duration (279 days) and cost ($1.34M).
  • Converged efficiently in an average of 118 iterations.

Conclusions:

  • MOAOO is the inaugural multi-objective variant of AOO, offering effective collaborative optimization for construction project design.
  • The algorithm overcomes limitations of conventional methods, providing practical value in construction scheduling.
  • MOAOO offers a robust and efficient solution for complex, multi-objective engineering management challenges.