[go: up one dir, main page]

Lim et al., 2003 - Google Patents

Designing guide-path networks for automated guided vehicle system by using the Q-learning technique

Lim et al., 2003

Document ID
5086959756346183821
Author
Lim J
Lim J
Yoshimoto K
Kim K
Takahashi T
Publication year
Publication venue
Computers & industrial engineering

External Links

Snippet

This paper suggests a Q-learning technique for designing guide-path networks for automated guided vehicle systems. This study uses the total travel time as the decision criteria for constructing guide-path layouts. The Q-learning technique is applied to the …
Continue reading at www.sciencedirect.com (other versions)

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
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • 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
    • G06Q10/06316—Sequencing of tasks or work
    • 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"
    • G06Q10/047—Optimisation of routes, e.g. "travelling salesman problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/26—Navigation; Navigational instruments not provided for in preceding groups specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3484—Personalized, e.g. from learned user behaviour or user-defined profiles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/26—Navigation; Navigational instruments not provided for in preceding groups specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/02—Knowledge representation
    • G06N5/022—Knowledge engineering, knowledge acquisition
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/26—Navigation; Navigational instruments not provided for in preceding groups specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3407—Route searching; Route guidance specially adapted for specific applications

Similar Documents

Publication Publication Date Title
Chen et al. Reliable shortest path finding in stochastic networks with spatial correlated link travel times
Hoogendoorn et al. Dynamic user-optimal assignment in continuous time and space
Xiao et al. Adaptive vehicle navigation with en route stochastic traffic information
Ghannadpour et al. A multi-objective vehicle routing and scheduling problem with uncertainty in customers’ request and priority
Fontecha et al. Combined maintenance and routing optimization for large-scale sewage cleaning
Noh et al. Hyperpaths in network based on transit schedules
JP5376465B2 (en) Congestion situation prediction program, computer-readable recording medium recording congestion situation prediction program and congestion situation prediction apparatus, navigation program, computer-readable recording medium recording navigation program, and navigation apparatus
Kumar et al. Adaptive park-and-ride choice on time-dependent stochastic multimodal transportation network
Capali et al. A multi-objective meta-heuristic approach for the transit network design and frequency setting problem
Amores et al. A proactive route planning approach to navigation errors
Redmond et al. Reliability in public transit networks considering backup itineraries
Neumann The shortest path problem with uncertain information in transport networks
Lim et al. Designing guide-path networks for automated guided vehicle system by using the Q-learning technique
Lim et al. A construction algorithm for designing guide paths of automated guided vehicle systems
Son Pham et al. Advancing large-scale cement vehicle distribution: the modified salp swarm algorithm
Crişan et al. Computational intelligence for solving difficult transportation problems
Higuera et al. Multiagent reinforcement learning applied to traffic light signal control
Vogiatzis et al. Combinatorial optimization in transportation and logistics networks
Tang et al. Modeling routing behavior learning process for vacant taxis in a congested urban traffic network
Nguyen Van et al. Novel online routing algorithms for smart people‐parcel taxi sharing services
JP7593420B2 (en) Route design system, cost function learning device, design route output device, method and program
Folsom et al. Dynamic routing of heterogeneous users after traffic disruptions under a mixed information framework
Turky et al. Deep learning assisted memetic algorithm for shortest route problems
Ismail et al. Application of ant colony optimization for the shortest path problem of waste collection process
JPH09222852A (en) Device with cognitive map