Algorithmic Complexity Research on Foreign-related Tourism English Education and Talent Cultivation Models in the Context of Free Trade Port DOI Open Access

Rulin Chen,

Peixu Hou,

Cheng Huang

и другие.

Applied Mathematics and Nonlinear Sciences, Год журнала: 2024, Номер 9(1)

Опубликована: Янв. 1, 2024

Abstract In today’s booming development of free trade ports, China, as a big country inbound and outbound tourism, has put forward higher requirements for the talent cultivation mode foreign-related tourism English. This paper takes characteristics English entry point establishes practical teaching system four-in-one The multi-objective optimization model cultivating foreign talents is proposed, with objective function enhancing quality talents, corresponding constraints are set. solved using DQN model, strategy gradient algorithm-based training proposed. test conditions set, simulation experiments carried out, compared based on optimal scheme. loss obtained by after 1700 iterations fluctuates between [0.015,0.019], when period set to 2 years, cumulative return can reach 623.87%, maximum retracement only - 5.457%. program’s average score 14.1 points than ordinary version. Foreign-related needs be fully integrated actual demand talent, faculty policy guidelines help enhance training.

Язык: Английский

A Q-Learning based NSGA-II for dynamic flexible job shop scheduling with limited transportation resources DOI

Rensheng Chen,

Bin Wu, Hua Wang

и другие.

Swarm and Evolutionary Computation, Год журнала: 2024, Номер 90, С. 101658 - 101658

Опубликована: Июль 18, 2024

Язык: Английский

Процитировано

15

Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions DOI

Maziyar Khadivi,

Todd Charter, Marjan Yaghoubi

и другие.

Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 110856 - 110856

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1

Tabu search based on novel neighborhood structures for solving job shop scheduling problem integrating finite transportation resources DOI

Youjie Yao,

Lin Gui, Xinyu Li

и другие.

Robotics and Computer-Integrated Manufacturing, Год журнала: 2024, Номер 89, С. 102782 - 102782

Опубликована: Май 14, 2024

Язык: Английский

Процитировано

9

Knowledge-based multi-objective evolutionary algorithm for energy-efficient flexible job shop scheduling with mobile robot transportation DOI

Youjie Yao,

Qingzheng Wang, Cuiyu Wang

и другие.

Advanced Engineering Informatics, Год журнала: 2024, Номер 62, С. 102647 - 102647

Опубликована: Июнь 19, 2024

Язык: Английский

Процитировано

9

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

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 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.

Язык: Английский

Процитировано

0

A knowledge-driven memetic algorithm for distributed green flexible job shop scheduling considering the endurance of machines DOI
Libao Deng, Yixuan Qiu,

Yuanzhu Di

и другие.

Applied Soft Computing, Год журнала: 2025, Номер 170, С. 112697 - 112697

Опубликована: Янв. 6, 2025

Язык: Английский

Процитировано

0

R-DMDQN: A rule embedding based dynamic multi-objective deep Q-network for mass-individualized production scheduling of printed circuit board DOI
Chunrong Pan, Teng Yu, Zhengchao Liu

и другие.

Journal of Manufacturing Systems, Год журнала: 2025, Номер 79, С. 466 - 483

Опубликована: Фев. 12, 2025

Язык: Английский

Процитировано

0

Deep reinforcement learning-based memetic algorithm for solving dynamic distributed green flexible job shop scheduling problem with finite transportation resources DOI
Xinxin Zhou, Feimeng Wang, Bin Wu

и другие.

Swarm and Evolutionary Computation, Год журнала: 2025, Номер 94, С. 101885 - 101885

Опубликована: Фев. 21, 2025

Язык: Английский

Процитировано

0

Research on dynamic job shop scheduling problem with AGV based on DQN DOI
Zhengfeng Li,

Wanfa Gu,

Huichao Shang

и другие.

Cluster Computing, Год журнала: 2025, Номер 28(4)

Опубликована: Фев. 25, 2025

Язык: Английский

Процитировано

0

Categorized Attention Based Hierarchical-agents Reinforcement Learning for Multi-objective Dynamic Job Shop Scheduling Problem With Machine Deterioration DOI
Yibing Li,

X. Liang,

Jun Guo

и другие.

Applied Soft Computing, Год журнала: 2025, Номер unknown, С. 113032 - 113032

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0