Multi-Objective Optimization of Short-Inverted Transport Scheduling Strategy Based on Road–Railway Intermodal Transport DOI Open Access
Dudu Guo,

Yinuo Su,

Xiaojiang Zhang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(15), P. 6310 - 6310

Published: July 24, 2024

This study focuses on the ‘short-inverted transportation’ scenario of intermodal transport. It proposes a vehicle unloading reservation mechanism to optimize point-of-demand scheduling system for inefficiency transport due complexity and uncertainty strategy. paper establishes strategy optimization model minimize cost short backhaul obtain shortest delivery time window designs hybrid NSGWO algorithm suitable multi-objective solve problem. The incorporates Non-dominated Sorting Genetic Algorithm II (NSGA-II) based Grey Wolf Optimizer (GWO) algorithm, compensating single algorithm’s premature convergence. experiment selects logistics carrier’s actual road–rail short-inverted data compares verifies above data. results show that scheme obtained by this can save 41.01% shorten total 46.94% compared with original scheme, which effectively protect enterprise’s economic benefits while achieving timely delivery. At same time, optimized plan resulted in lower number vehicles, positively impacted sustainability green logistics.

Language: Английский

Novel Sustainable Green Transportation: A Neutrosophic Multi-Objective Model Considering Various Factors in Logistics DOI

Kalaivani Kaspar,

K. Palanivel

Sustainable Computing Informatics and Systems, Journal Year: 2025, Volume and Issue: unknown, P. 101096 - 101096

Published: Feb. 1, 2025

Language: Английский

Citations

2
Maintenance-driven multi-stage joint optimization considering spare parts production, distribution and imperfect maintenance DOI
Qiang Luo, Qianwang Deng, Huining Zhuang

et al.

Reliability Engineering & System Safety, Journal Year: 2025, Volume and Issue: unknown, P. 110799 - 110799

Published: Jan. 1, 2025

Language: Английский

Citations

1
Data-driven automated job shop scheduling optimization considering AGV obstacle avoidance DOI Creative Commons
Qi Tang, Huan Wang

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 2, 2025

The production stage of an automated job shop is closely linked to the guided vehicle (AGV), which needs be planned in integrated manner achieve overall optimization. In order improve collaboration between stages and AGV operation system, a two-layer scheduling optimization model proposed for simultaneous decision making batching problems, sequences obstacle avoidance. Under automatic path seeking mode, this paper adopts data-driven Bayesian network method portray transportation time AGVs based on historical data control uncertainty AGVs. Meanwhile, window established risk delay, constructed optimize AGV. To solve model, we design improved particle swarm algorithm combining genetic operators, crossover operators elite retention operator. results show that can effectively system within floor, successfully actual scale case enhance effectiveness system.

Language: Английский

Citations

0
Applications of simulated annealing algorithm in mathematical modelling for scheduling problems DOI Creative Commons

Ling Zhu,

Yuhui Zhu

Journal of Computational Methods in Sciences and Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 7, 2025

Scheduling problems are common in many fields, with project planning, industrial, operations management, and service establishment. These involve the advanced distribution of resources across tasks to exploit exact objectives within predetermined bounds. This study examines an enhanced simulated annealing (ESA) algorithm for addressing dynamic scheduling challenges job shops, particularly context random arrivals frequently encountered manufacturing environments. programming methodology seeks minimize three primary targets: machine sequence variation, make-span divergence from original schedule, discontinuity rate newly delivered during processing. In rescheduling horizon, ongoing processes handled as resource allocation (DRA). Tactics involved ESA include a modified cooling adaptive temperature regulation, solution approval criterion that considers DRA. The experimental results indicate effectively solves shop problems. proposed has high completion 95%, task acceptance 92%, arrival predictability 85%, 8%, return on investment 25%. highlight effectiveness achieving optimal solutions, underscoring its potential practical applications settings.

Language: Английский

Citations

0
Multi-Objective Optimization of Short-Inverted Transport Scheduling Strategy Based on Road–Railway Intermodal Transport DOI Open Access
Dudu Guo,

Yinuo Su,

Xiaojiang Zhang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(15), P. 6310 - 6310

Published: July 24, 2024

This study focuses on the ‘short-inverted transportation’ scenario of intermodal transport. It proposes a vehicle unloading reservation mechanism to optimize point-of-demand scheduling system for inefficiency transport due complexity and uncertainty strategy. paper establishes strategy optimization model minimize cost short backhaul obtain shortest delivery time window designs hybrid NSGWO algorithm suitable multi-objective solve problem. The incorporates Non-dominated Sorting Genetic Algorithm II (NSGA-II) based Grey Wolf Optimizer (GWO) algorithm, compensating single algorithm’s premature convergence. experiment selects logistics carrier’s actual road–rail short-inverted data compares verifies above data. results show that scheme obtained by this can save 41.01% shorten total 46.94% compared with original scheme, which effectively protect enterprise’s economic benefits while achieving timely delivery. At same time, optimized plan resulted in lower number vehicles, positively impacted sustainability green logistics.

Language: Английский

Citations

2