Niu, 2021 - Google Patents
Multi Skill Human Resource Group Intelligent Scheduling Method Based on Reinforcement LearningNiu, 2021
- Document ID
- 12432145030473129924
- Author
- Niu L
- Publication year
- Publication venue
- 2021 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI)
External Links
Snippet
To improve the intelligence of multiskilled human resource group scheduling, a multiskilled human resource group intelligent scheduling method based on reinforcement learning is proposed. It is divided into six steps to build an enterprise project group, mainly including the …
- 230000002787 reinforcement 0 title abstract description 23
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
- G06Q10/0631—Resource planning, allocation or scheduling for a business operation
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
- G06F9/46—Multiprogramming arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce, e.g. shopping or e-commerce
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Asim et al. | A review on computational intelligence techniques in cloud and edge computing | |
Ni et al. | A multi-graph attributed reinforcement learning based optimization algorithm for large-scale hybrid flow shop scheduling problem | |
CN104842564B (en) | A kind of 3 D-printing multitask Optimization Scheduling based on NSGA II | |
CN104065745A (en) | Cloud computing dynamic resource scheduling system and method | |
CN117596246B (en) | Method and system for scheduling workflow of computing power network based on heterogeneous resource measurement characteristics | |
Nesmachnow et al. | Holistic multiobjective planning of datacenters powered by renewable energy | |
Méndez-Hernández et al. | A multi-objective reinforcement learning algorithm for jssp | |
Chen et al. | A collaborative scheduling method for cloud computing heterogeneous workflows based on deep reinforcement learning | |
CN116643877A (en) | Computing power resource scheduling method, training method and system of computing power resource scheduling model | |
Gao et al. | A multi-objective service composition method considering the interests of tri-stakeholders in cloud manufacturing based on an enhanced jellyfish search optimizer | |
Xu et al. | Energy-driven virtual network embedding algorithm based on enhanced bacterial foraging optimization | |
Nesmachnow et al. | Controlling datacenter power consumption while maintaining temperature and QoS levels | |
Liu et al. | 5G/B5G Network Slice Management via Staged Reinforcement Learning | |
CN115421885A (en) | Distributed multi-target cloud task scheduling method and device and cloud service system | |
Ferrucci et al. | Decentralized replica management in latency-bound edge environments for resource usage minimization | |
Trabelsi et al. | Leveraging evolutionary algorithms for dynamic multi-objective optimization scheduling of multi-tenant smart home appliances | |
Niu | Multi Skill Human Resource Group Intelligent Scheduling Method Based on Reinforcement Learning | |
Zhang et al. | Survey on task scheduling optimization strategy under multi-cloud environment | |
Zhang et al. | Dynamic decision-making for knowledge-enabled distributed resource configuration in cloud manufacturing considering stochastic order arrival | |
Xie et al. | A Two‐Workshop Collaborative, Integrated Scheduling Algorithm considering the Prescheduling of the Root‐Subtree Processes | |
Dong et al. | Optimization of service scheduling in computing force network | |
CN111260252A (en) | Power communication network field operation and maintenance work order scheduling method | |
Prado et al. | On providing quality of service in grid computing through multi-objective swarm-based knowledge acquisition in fuzzy schedulers | |
Tong et al. | D2op: A fair dual-objective weighted scheduling scheme in internet of everything | |
CN115396491A (en) | Multilayer heterogeneous analysis method of service ecosystem |