Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm DOI Creative Commons
Dawei Wang, Bo Gao, Lei Zhang

и другие.

Energy Science & Engineering, Год журнала: 2025, Номер unknown

Опубликована: Март 30, 2025

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 of electric highway engineering projects within roadbed construction. The research considers multiple earthmoving processes optimizes working time each piece equipment, taking into account capacity speed limited week. is further contextualized by use regional time‐of‐use (TOU) electricity pricing. A sophisticated optimization model developed to simulate optimal machinery operation, striking balance between energy consumption work paper introduces an innovative algorithm, improved crested porcupine optimizer (ICPO), which incorporates Latin hypercube sampling for population initialization. To enhance algorithmic effectiveness, combined strategy parallel compact processing employed. approach reduces number iterations required consequently lowers consumption. Rigorous analysis comparison with existing algorithms demonstrate that ICPO iteration count financial expenditure. Simulation results validate accuracy practicality proposed showing reduction over 7%

Язык: Английский

Integrated heterogeneous graph and reinforcement learning enabled efficient scheduling for surface mount technology workshop DOI
Biao Zhang, Hongyan Sang, Chao Lu

и другие.

Information Sciences, Год журнала: 2025, Номер unknown, С. 122023 - 122023

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Production-logistics collaborative scheduling in dynamic flexible job shops using nested-hierarchical deep reinforcement learning DOI
Jiaxuan Shi, Fei Qiao, Juan Liu

и другие.

Advanced Engineering Informatics, Год журнала: 2025, Номер 65, С. 103195 - 103195

Опубликована: Март 4, 2025

Язык: Английский

Процитировано

0

Distributed heterogeneous flexible job-shop scheduling problem considering automated guided vehicle transportation via improved deep Q network DOI
Minghai Yuan, S. Lu, Liang Zheng

и другие.

Swarm and Evolutionary Computation, Год журнала: 2025, Номер unknown, С. 101902 - 101902

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Harnessing heterogeneous graph neural networks for Dynamic Job-Shop Scheduling Problem solutions DOI
Chien‐Liang Liu, P.S. Weng, Chun-Jan Tseng

и другие.

Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 111060 - 111060

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm DOI Creative Commons
Dawei Wang, Bo Gao, Lei Zhang

и другие.

Energy Science & Engineering, Год журнала: 2025, Номер unknown

Опубликована: Март 30, 2025

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 of electric highway engineering projects within roadbed construction. The research considers multiple earthmoving processes optimizes working time each piece equipment, taking into account capacity speed limited week. is further contextualized by use regional time‐of‐use (TOU) electricity pricing. A sophisticated optimization model developed to simulate optimal machinery operation, striking balance between energy consumption work paper introduces an innovative algorithm, improved crested porcupine optimizer (ICPO), which incorporates Latin hypercube sampling for population initialization. To enhance algorithmic effectiveness, combined strategy parallel compact processing employed. approach reduces number iterations required consequently lowers consumption. Rigorous analysis comparison with existing algorithms demonstrate that ICPO iteration count financial expenditure. Simulation results validate accuracy practicality proposed showing reduction over 7%

Язык: Английский

Процитировано

0