Optimization on construction machinery considering sequence-dependent setup times and personnel fatigue based on the...

Area of Science:

• Civil Engineering
• Operations Research
• Construction Management

Background:

• Construction machinery scheduling is complex, impacted by factors like personnel fatigue and sequence-dependent setup times.
• Existing optimization models often struggle to efficiently address these multifaceted challenges in roadbed projects.
• Maximizing equipment utilization and minimizing operational costs remain critical goals in construction engineering.

Purpose of the Study:

• To develop and validate a novel optimization model and algorithm for construction machinery scheduling in roadbed projects.
• To integrate considerations of personnel fatigue and sequence-dependent setup times into the scheduling optimization.
• To enhance equipment utilization efficiency and reduce overall project expenditure.

Main Methods:

• Development of a sophisticated optimization model for machinery operation simulation.
• Introduction of an improved hybrid gray wolf and whale algorithm (IHWGWO) incorporating a penalty function.
• Comparative analysis of the proposed IHWGWO against existing algorithms through rigorous simulations.

Main Results:

• The IHWGWO algorithm demonstrated a significant reduction in the number of optimization iterations.
• The proposed method led to substantial cuts in financial expenditure compared to traditional algorithms.
• Simulation outcomes validated the accuracy and practicality of the IHWGWO for construction machinery scheduling.

Conclusions:

• The IHWGWO presents a promising and effective approach for optimizing construction machinery scheduling.
• Addressing personnel fatigue and setup times concurrently leads to improved operational efficiency.
• The developed model and algorithm offer practical solutions for enhancing efficiency and reducing costs in roadbed construction projects.