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Utilizing artificial intelligence to solving time - cost - quality trade-off problem.

Pham Vu Hong Son1, Luu Ngoc Quynh Khoi2

  • 1Construction Engineering & Management Department, Ho Chi Minh City University of Technology (HCMUT), Vietnam National University, 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, 700000, Vietnam. pvhson@hcmut.edu.vn.

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The Slime Mold Algorithm (SMA) effectively optimizes construction project trade-offs. This novel approach outperforms existing methods in solving complex time-cost-quality challenges.

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Area of Science:

  • Optimization Algorithms
  • Construction Project Management
  • Operations Research

Background:

  • Construction projects face complex trade-offs between time, cost, and quality.
  • Existing optimization algorithms may lack the flexibility or efficiency for these multi-objective problems.

Purpose of the Study:

  • To introduce and evaluate the Slime Mold Algorithm (SMA) for the time-cost-quality trade-off problem in construction.
  • To compare SMA's performance against established multi-objective optimization algorithms.

Main Methods:

  • Implementation of the Slime Mold Algorithm (SMA) for processing project data.
  • Comparative analysis of SMA against Opposition-based Multiple Objective Differential Evolution, Non-dominated sorting genetic algorithm, Multiple objective particle swarm optimization, Multiple objective differential evolution, and Chaotic initialized multiple objective differential evolution (CAMODE).

Main Results:

  • The Slime Mold Algorithm (SMA) demonstrated superior performance in generating diversification measures for case studies.
  • SMA produced better outcomes compared to all evaluated traditional algorithms.

Conclusions:

  • The Slime Mold Algorithm (SMA) is a flexible and efficient tool for addressing time-cost-quality trade-offs in construction.
  • SMA shows significant potential and efficiency for complex optimization problems in project management.