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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Wiley
2025-06-01
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| Series: | Energy Science & Engineering |
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| 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. |
| format | Article |
| id | doaj-art-86792b1dd5a94bfcba71bb99d0f87984 |
| institution | DOAJ |
| issn | 2050-0505 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Energy Science & Engineering |
| 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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