Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm

ABSTRACT Optimization scheduling plays a pivotal role in construction projects, significantly influencing both the overall project schedule and its efficiency. This study focuses on optimizing the scheduling of electric highway engineering projects within roadbed construction. The research considers...

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Main Authors: Dawei Wang, Bo Gao, Lei Zhang
Format: Article
Language:English
Published: Wiley 2025-06-01
Series:Energy Science & Engineering
Subjects:
Online Access:https://doi.org/10.1002/ese3.70080
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author Dawei Wang
Bo Gao
Lei Zhang
author_facet Dawei Wang
Bo Gao
Lei Zhang
author_sort Dawei Wang
collection DOAJ
description ABSTRACT Optimization scheduling plays a pivotal role in construction projects, significantly influencing both the overall project schedule and its efficiency. This study focuses on optimizing the scheduling of electric highway engineering projects within roadbed construction. The research considers multiple earthmoving processes and optimizes the working time of each piece of equipment, taking into account its capacity and speed within a limited working week. The study is further contextualized by the use of regional time‐of‐use (TOU) electricity pricing. A sophisticated optimization model is developed to simulate optimal machinery operation, striking a balance between energy consumption and work efficiency. This paper introduces an innovative algorithm, the improved crested porcupine optimizer (ICPO), which incorporates Latin hypercube sampling for population initialization. To enhance algorithmic effectiveness, a combined strategy of parallel and compact processing is employed. This approach reduces the number of iterations required for optimization and consequently lowers energy consumption. Rigorous analysis and comparison with existing algorithms demonstrate that ICPO significantly reduces both iteration count and financial expenditure. Simulation results validate the accuracy and practicality of the proposed model and algorithm, showing a reduction of over 7% in both engineering time and energy consumption.
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spelling doaj-art-86792b1dd5a94bfcba71bb99d0f879842025-08-20T03:11:14ZengWileyEnergy Science & Engineering2050-05052025-06-011362973298610.1002/ese3.70080Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer AlgorithmDawei Wang0Bo Gao1Lei Zhang2Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education Wuhan University of Science and Technology Wuhan ChinaCCCC Second Highway Consultants Company Limited Wuhan ChinaKey Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education Wuhan University of Science and Technology Wuhan ChinaABSTRACT Optimization scheduling plays a pivotal role in construction projects, significantly influencing both the overall project schedule and its efficiency. This study focuses on optimizing the scheduling of electric highway engineering projects within roadbed construction. The research considers multiple earthmoving processes and optimizes the working time of each piece of equipment, taking into account its capacity and speed within a limited working week. The study is further contextualized by the use of regional time‐of‐use (TOU) electricity pricing. A sophisticated optimization model is developed to simulate optimal machinery operation, striking a balance between energy consumption and work efficiency. This paper introduces an innovative algorithm, the improved crested porcupine optimizer (ICPO), which incorporates Latin hypercube sampling for population initialization. To enhance algorithmic effectiveness, a combined strategy of parallel and compact processing is employed. This approach reduces the number of iterations required for optimization and consequently lowers energy consumption. Rigorous analysis and comparison with existing algorithms demonstrate that ICPO significantly reduces both iteration count and financial expenditure. Simulation results validate the accuracy and practicality of the proposed model and algorithm, showing a reduction of over 7% in both engineering time and energy consumption.https://doi.org/10.1002/ese3.70080construction schedulingenergy consumptionimproved hybrid algorithmoperation machinery
spellingShingle Dawei Wang
Bo Gao
Lei Zhang
Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm
Energy Science & Engineering
construction scheduling
energy consumption
improved hybrid algorithm
operation machinery
title Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm
title_full Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm
title_fullStr Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm
title_full_unstemmed Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm
title_short Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm
title_sort optimization on electric construction machinery considering time of use electricity price based on the improved crested porcupine optimizer algorithm
topic construction scheduling
energy consumption
improved hybrid algorithm
operation machinery
url https://doi.org/10.1002/ese3.70080
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AT leizhang optimizationonelectricconstructionmachineryconsideringtimeofuseelectricitypricebasedontheimprovedcrestedporcupineoptimizeralgorithm