Train Scheduling in High-Speed Railway Freight Transportation Using a Hyper-Heuristic Algorithm DOI

Mingli Zhao,

Shaoquan Ni, Zhi-Gang Du

et al.

Transportation Research Record Journal of the Transportation Research Board, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 31, 2024

The rapidly growing demand for high-quality logistics services, coupled with the expansion of high-speed rail networks, has presented both challenges and opportunities in realm freight transportation. Because intricacies transportation inherent complexities within passenger-train operations, addressing market demands proves to be challenging. This study focuses on optimizing passenger–freight collaboration train timetables. Express cargo is typically transported either by incorporating it into planned schedules or introducing additional trains, which can disrupt original passenger transport arrangements. To mitigate such disruptions, a buffer time allocated compensate any disturbances, thereby transforming delivery timeframe streamlined car-flow transit deadline. address these challenges, we developed optimization model was then solved using bacterial foraging-based hyper-heuristic algorithm known its global capabilities distribution-centric approach. In comparison existing studies algorithms modeling, considering parameters as average fitness running time, proposed demonstrated superior efficiency.

Language: Английский

Implementation and efficient evaluation of backpropagation network training algorithms in parametric simulations of soil hydraulic conductivity curve DOI

Mostafa Rastgou,

Yong He, Qianjing Jiang

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 636, P. 131302 - 131302

Published: May 9, 2024

Language: Английский

Citations

4
AI-powered MMI fiber sensors for wide-range refractive index detection using neural networks algorithm DOI

Nurul Farah Adilla Zaidi,

Muhammad Yusof Mohd Noor, Nur Najahatul Huda Saris

et al.

Optical Fiber Technology, Journal Year: 2025, Volume and Issue: 90, P. 104113 - 104113

Published: Jan. 5, 2025

Language: Английский

Citations

0
Decomposition combining averaging seasonal-trend with singular spectrum analysis and a marine predator algorithm embedding Adam for time series forecasting with strong volatility DOI
M Wang,

Yu Meng,

Lei Sun

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 126864 - 126864

Published: Feb. 1, 2025

Language: Английский

Citations

0
A Hybrid Parallel Willow Catkin Optimization Algorithm Applied for Engineering Optimization Problems DOI Creative Commons
Shu‐Chuan Chu,

Buyue Guo,

bing sun

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 102396 - 102415

Published: Jan. 1, 2024

The Willow Catkin Optimization Algorithm (WCO) is a newly proposed meta-heuristic algorithm in recent years that has simple structure and excellent optimization searching ability, but the WCO could benefit from improvements both convergence speed solution diversity. In this paper, parallel technology introduced into algorithm, by proposing two new communication strategies, Random Mean (RM) method Optimal Flight (OF) method, goal to utilize all information obtained each subpopulation strategy enhance algorithm's performance. Additionally, been hybridized with Differential Evolution (DE), mutation mechanism improve diversity of solutions. resulting called Hybrid Parallel (HPWCO). HPWCO tested on CEC2017 benchmark function set applied five real-world engineering problems constraints, experimental results were compared three types algorithms: classical algorithm. indicate performs excellently.

Language: Английский

Citations

2
Adaptive crossover-based marine predators algorithm for global optimization problems DOI Creative Commons
Shaymah Akram Yasear

Journal of Computational Design and Engineering, Journal Year: 2024, Volume and Issue: 11(4), P. 124 - 150

Published: June 26, 2024

Abstract The Marine Predators Algorithm (MPA) is a swarm intelligence algorithm developed based on the foraging behavior of ocean’s predators. This has drawbacks including, insufficient population diversity, leading to trapping in local optima and poor convergence. To mitigate these drawbacks, this paper introduces an enhanced MPA Adaptive Sampling with Maximin Distance Criterion (AM) horizontal vertical crossover operators – i.e., Crossover-based (AC-MPA). AM approach used generate diverse well-distributed candidate solutions. Whereas maintain diversity during search process. performance AC-MPA was tested using 51 benchmark functions from CEC2017, CEC2020, CEC2022, varying degrees dimensionality, findings are compared those its basic version, variants, numerous well-established metaheuristics. Additionally, 11 engineering optimization problems were utilized verify capabilities handling real-world problems. clearly show that performs well terms solution accuracy, convergence, robustness. Furthermore, proposed demonstrates considerable advantages solving problems, proving effectiveness adaptability.

Language: Английский

Citations

1
DMT-OMPA: Innovative applications of an efficient adversarial Marine Predators Algorithm based on dynamic matrix transformation in engineering design optimization DOI
Z. Zhang, Shu‐Chuan Chu, Trong-The Nguyen

et al.

Computer Methods in Applied Mechanics and Engineering, Journal Year: 2024, Volume and Issue: 431, P. 117247 - 117247

Published: July 29, 2024

Language: Английский

Citations

0
A Multi-Strategy Enhanced Marine Predator Algorithm for Global Optimization and UAV Swarm Path Planning DOI Creative Commons
G. Gu, Haitao Li, Cunsheng Zhao

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 112095 - 112115

Published: Jan. 1, 2024

Language: Английский

Citations

0
Application on Power system Economic Dispatch of Marine Predator Algorithm Improved by Asymmetric Information Exchange DOI Creative Commons
Cheng Yang, Xiaoliang Zheng, Jiwen Wang

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(17), P. e36928 - e36928

Published: Aug. 26, 2024

The solution to the economic dispatch (ED) problem for power systems allows sector reduce operating costs. However, ED is a complex nonlinear and nonconvex optimization whose requires powerful algorithms. We propose new version of Marine Predator Algorithm (MPA), called IMPA, solving problems. algorithm introduces an asymmetric information exchange (AIE) mechanism, which not only accelerates escape local optima but also enriches diversity search. In this work, 12 benchmark functions were used test performance proposed IMPA. Then, IMPA was solve engineering system containing 6, 13, 40, 140 units. minimum average costs searched by are 1657962.7265$/h 1657962.7265$/h, they much lower than results MPA NMPA, means that our improved improves large-scale systems. show solutions obtained more competitive those provides additional cost reduction system.

Language: Английский

Citations

0
Optimization Analysis of Loss Function Related to Spot Price of Gansu Power Based on RNN DOI

乐 马

Computer Science and Application, Journal Year: 2024, Volume and Issue: 14(10), P. 110 - 126

Published: Jan. 1, 2024

Language: Английский

Citations

0
Train Scheduling in High-Speed Railway Freight Transportation Using a Hyper-Heuristic Algorithm DOI

Mingli Zhao,

Shaoquan Ni, Zhi-Gang Du

et al.

Transportation Research Record Journal of the Transportation Research Board, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 31, 2024

The rapidly growing demand for high-quality logistics services, coupled with the expansion of high-speed rail networks, has presented both challenges and opportunities in realm freight transportation. Because intricacies transportation inherent complexities within passenger-train operations, addressing market demands proves to be challenging. This study focuses on optimizing passenger–freight collaboration train timetables. Express cargo is typically transported either by incorporating it into planned schedules or introducing additional trains, which can disrupt original passenger transport arrangements. To mitigate such disruptions, a buffer time allocated compensate any disturbances, thereby transforming delivery timeframe streamlined car-flow transit deadline. address these challenges, we developed optimization model was then solved using bacterial foraging-based hyper-heuristic algorithm known its global capabilities distribution-centric approach. In comparison existing studies algorithms modeling, considering parameters as average fitness running time, proposed demonstrated superior efficiency.

Language: Английский

Citations

0