# Optimization on construction machinery considering sequence-dependent setup times and personnel fatigue based on the improved gray wolf and whale algorithm

## TL;DR

This paper introduces a new algorithm to optimize construction machinery scheduling by considering setup times and worker fatigue, improving efficiency and reducing costs.

## Contribution

The novel IHWGWO algorithm combines gray wolf and whale optimization with a penalty function to address scheduling challenges in construction.

## Key findings

- The IHWGWO algorithm reduces the number of iterations needed for optimization.
- The proposed method lowers energy consumption and financial expenditure in construction projects.
- Simulation results validate the model's accuracy and practicality in real-world scenarios.

## Abstract

In this study, the optimization of construction machinery scheduling within roadbed construction projects is explored, taking into account both personnel fatigue and sequence-dependent setup times. A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. This algorithm reduces the number of iterations required for optimization and, subsequently, cuts down on energy consumption. Through rigorous analysis and comparison with existing algorithms, the proposed IHWGWO demonstrates a significant reduction in both iteration count and financial expenditure. Simulation outcomes confirm the accuracy and practicality of the model and algorithm, establishing a promising new approach for scheduling in construction engineering.