Title: Scheduling and Routing Algorithms for AGVs: A Survey
1Scheduling and Routing Algorithms for AGVs A
Survey
Ling Qiu Wen-Jing Hsu Shell-Ying Huang Han
Wang
presented by Oguz Atan
2OUTLINE
- Introduction
- Problem of Scheduling Routing
- Similar Problems
- Classification of Algorithms
- Future Directions of Research
- Concluding Remarks
3INTRODUCTION
- AGVs are popular in
- Automatic Materials Handling Systems
- Flexible Manufacturing Systems
- Container Handling Applications
- AGVs are composed of
- Hardware AGVs, paths, controllers, sensors,
etc. - Software algorithms for managing the hardware
4INTRODUCTION
- Great number of tasks
- Large Fleet
- Many hazards, i.e., congestion, deadlocks
- Non-trivial scheduling / routing
- Cancellation of AGV system deployment
5THE SCHEDULING PROBLEM
- dispatches a set of AGVs
- realizes a batch of pickup/drop-off jobs
- considers a number of constraints
- deadlines
- priority
- tries to achieve certain goals
- minimizing the number of AGVs
- minimizing the total travel time
6THE ROUTING PROBLEM
- After Scheduling Decision is Made
- finds a suitable route for every AGV
- from origin to destination
- based on the traffic situation
- considering a certain goal
- shortest-distance path
- shortest-time path
- minimal energy path
7THE ROUTING PROBLEM
- Routing Decision involves two issues
- whether there exists a route
- indirect transfer system
- whether the selected route is feasible
- congestion
- conflicts
- deadlocks
8THE PROBLEM
- A system with few vehicles jobs
- trivial scheduling algorithms are OK, i.e., FCFS
- nearest idle vehicle
- routing is main issue
- A system with many jobs limited number of
vehicles - many hazards collusion, congestion, livelock,
deadlock - nontrivial scheduling routing
9SIMILAR PROBLEMS
- A variation of Vehicle Routing Problem (VRP)
- Bodin and Golden, 1981 Bodin et al., 1983
- significant distinctions
- length of a vehicle
- load capacity of a path
- shortest time path vs. shortest distance path
- revision of existing layout
10SIMILAR PROBLEMS
- A variation of Path Problems in Graph Theory
- shortest path problem
- Hamiltonian-type problem
- main differences
- time-critical problem
- existence of an optimal path
- when how an AGV gets to its destination
- graph problem disregards
- system control mechanism
- path layout
11SIMILAR PROBLEMS
- A variation of Routing Electronic Data in a
Network - some analogies
- AGVs / data packets
- paths / data links
- traffic control devices / routers
- some distinctions
- time for transportation a function of distance
or not? - in case of failure discard re-send
12CLASSIFICATION OF ALGORITHMS
- 1) Algorithms for General Path Topology
- treats the problem as a graph theory problem
- 2) Path Optimization
- considers optimization of path network
- 3) Algorithms for Specific Path Topologies
- single-loop, multi-loops, meshes, etc.
- 4) Dedicated Scheduling Algorithms
- without consideration of routing
131) Algorithms for General Path Topology 2) Path
Optimization 3) Algorithms for Specific Path
Topologies 4) Dedicated Scheduling Algorithms
14Algorithms for General Path Topology
- Focus mainly on finding the feasible routes
- do not consider the topological characteristics
- offer universal routing solutions
- aim is to give conflict-free and shortest-time
routings - Methods used can be put in three categories
- static methods
- time-window based methods
- dynamic methods
151) Algorithms for General Path Topology static
methods time-window based methods dynamic
methods 2) Path Optimization 3) Algorithms for
Specific Path Topologies 4) Dedicated Scheduling
Algorithms
16Algorithms for General Path Topology
- Static Methods
- routing procedure using Dijkstras shortest path
algorithm
Broadbent et al., 1985 - matrix of path occupation times of vehicles
- potential conflicts are avoided a priori
- head-on conflicts find another shortest path
- head-to-tail junction conflicts slowing down
the latter - complexity of O(n2), n is P/D stations or
junctions
17Algorithms for General Path Topology
- Static Methods
- bidirectional path AGV systems are advantageous
- utilization of vehicles
- potential throughput efficiency
- improvement in productivity
- reduction in vehicles
- Egbelu and Tanchoco, 1986 Egbelu, 1987
- no algorithm is given to guarantee the optimal
routes
18Algorithms for General Path Topology
- Static Methods
- bidirectional flow path network
- partitioning shortest path (PSP) algorithm
- finds a route for new added AGV, without
changing previous - complexity O(n x a), a is of arcs (path
segments) - if a path is allocated to a vehicle, unusable
for others until
destination
is reached - may not find a path even if there exists one
- suitable for small networks with less AGVs
- Daniels, 1988
191) Algorithms for General Path Topology static
methods time-window based methods dynamic
methods 2) Path Optimization 3) Algorithms for
Specific Path Topologies 4) Dedicated Scheduling
Algorithms
20Algorithms for General Path Topology
- Time-window-based Methods
- in order to share the path network efficiently
- better path utilization
- labelling algorithm to find a shortest-time path
- single vehicle, bidirectional path network
- path segments as nodes, arcs between adjacent
segments - complexity of O(w2log w), w is time-windows of
all nodes - Huang et al., 1988
21Algorithms for General Path Topology
- Time-window-based Methods
- labelling algorithm to find a shortest-time path
- conflict-free shortest time routing in
bidirectional path network - based on Dijkstras shortest path algorithm
- free time-windows as nodes, arcs as reachability
among them - O(v4n2), v vehicles, n nodes, suitable for
small systems - Kim and Tanchoco, 1991
- later in 1993, using conservative myopic
strategy - one vehicle at a time, previous routes are
strictly respected - subsequent schedule made after the vehicle
becomes idle
221) Algorithms for General Path Topology static
methods time-window based methods dynamic
methods 2) Path Optimization 3) Algorithms for
Specific Path Topologies 4) Dedicated Scheduling
Algorithms
23Algorithms for General Path Topology
- Dynamic Methods
- in order to speed up the process of finding
routes - utilization of path segments determined during
routing - incremental route planning
- selects the next node for vehicle to visit until
destination - selected among adjacent nodes for shortest
travel time - optimal route not guaranteed, better for small
systems - Taghaboni and Tanchoco, 1995
24Algorithms for General Path Topology
- Dynamic Methods
- algorithm for an optimal integrated solution
- dispatching, conflict-free routing, scheduling
of AGVs - defines a partial transportation plan as a
schedule and a
route for
each vehicle - states are defined corresponding to partial
transportation plans - dynamic programming tries to find the best final
state - states is very large, some are eliminated,
vehicle limit is 2 - optimality of the solution is not guaranteed
- Langevin et al., 1995
251) Algorithms for General Path Topology 2) Path
Optimization 3) Algorithms for Specific Path
Topologies 4) Dedicated Scheduling Algorithms
26Path Optimization
- Since computation of finding optimal routes is
difficult - Optimize the path layout
- Optimize the distribution of P/D stations
- Three methods to formulate the problem
- 0-1 integer-programming model
- intersection graph method
- integer linear programming model
271) Algorithms for General Path Topology 2) Path
Optimization 0-1 integer-programming model
intersection graph method integer linear
programming model 3) Algorithms for Specific Path
Topologies 4) Dedicated Scheduling Algorithms
28Path Optimization
- 0-1 Integer Programming Model
- Gaskins and Tanchoco, 1987
- find the optimal unidirectional path network
- facility layout and P/D stations are given
- minimize the total travelling distance of loaded
vehicles - unloaded vehicles not considered
- a fleet of AGVs with same origin destination
every time - 0-1 variables may be very large, inefficient
computation
- Kaspi and Tanchoco, 1990
- use branchbound to reduce the computation
- worse quality, since not all possibilities are
enumerated
291) Algorithms for General Path Topology 2) Path
Optimization 0-1 integer-programming model
intersection graph method integer linear
programming model 3) Algorithms for Specific Path
Topologies 4) Dedicated Scheduling Algorithms
30Path Optimization
- Intersection Graph Method
- Sinriech and Tanchoco, 1991
- only a reduced subset of all nodes in path
network is considered - only the intersection nodes are used to find the
optimal solution - branches is only half of the main problem
- can be used in large systems
- since only intersection nodes are considered,
some optimal
solutions might be
missed
311) Algorithms for General Path Topology 2) Path
Optimization 0-1 integer-programming model
intersection graph method integer linear
programming model 3) Algorithms for Specific Path
Topologies 4) Dedicated Scheduling Algorithms
32Path Optimization
- Integer Linear Programming Model
- Goetz and Egbelu, 1990
- select the path and location of P/D stations
together - minimize the total distance traveled by loaded
unloaded AGVs - a heuristic algorithm is used to reduce the size
of the problem - can be used in large systems
- can be used in design of large path layouts
- issues of vehicle number routing control not
considered
331) Algorithms for General Path Topology 2) Path
Optimization 3) Algorithms for Specific Path
Topologies Linear Topology Loop Topology Mesh
Topology 4) Dedicated Scheduling Algorithms
34Algorithms for Specific Path Topologies
- Linear Topology
- Qui and Hsu, 2001
- schedule route a batch of AGVs concurrently
- bidirectional linear path layout
- freedom of conflicts is guaranteed
- size of the system does not effect the
efficiency of the algorithm - unrealistic synchronization requirements of
vehicles
351) Algorithms for General Path Topology 2) Path
Optimization 3) Algorithms for Specific Path
Topologies Linear Topology Loop Topology Mesh
Topology 4) Dedicated Scheduling Algorithms
36Algorithms for Specific Path Topologies
- Loop Topology
- only few vehicles run in the same direction
within a loop - simpler routing control, but lower system
throughput - Tanchoco and Sinriech, 1992
- finds the optimal closed single-loop path layout
- algorithm based on integer programming
- simple routing control
- vehicles running in same direction with uniform
speed - no intersections in the optimal single-loop
- vehicle limit is 10 / single-loop , not suitable
for large systems
37Algorithms for Specific Path Topologies
- Loop Topology
- Lin and Dgen, 1994
- algorithm for routing AGVs on non-overlapping
closed loops - P/D stations in each loop are served by a single
vehicle - transit areas located between adjacent loops
- task-list time-window algorithm used for
shortest travel time path - computation for routing is small
- system throughput is low, since single vehicle
in a loop - transfer devices are expensive, therefore cant
be a large system
38Algorithms for Specific Path Topologies
- Loop Topology
- Barad and Sinriech, 1998
- segmented floor topology (SFT)
- consisting of one or more zones
- each zone is separated into non-overlapping
segments - each segment served by a single vehicle moving
bidirectional - transfer buffers located at both ends of every
segment - transfer devices may be costly or time consuming
391) Algorithms for General Path Topology 2) Path
Optimization 3) Algorithms for Specific Path
Topologies Linear Topology Loop Topology Mesh
Topology 4) Dedicated Scheduling Algorithms
40Algorithms for Specific Path Topologies
- Mesh Topology
- container handling
- stacking yards arranged into rectangular blocks
- Hsu and Huang, 1994
- gave analysis of time complexities for some
routing operations - delivery, distribution, scattering,
accumulation, gathering, sorting - linear array, ring, binary tree, star, 2D mesh,
n-cube, etc. - upper bounds of time and space complexities are
O(n2) and O(n3)
41Algorithms for Specific Path Topologies
- Mesh Topology
- Qiu and Hsu, 2000
- n x n mesh-like topology
- can schedule route simultaneously up to 4n2
AGVs at one time - schedules AGVs batch by batch based on job
arrivals - AGVs get to destination in 3n steps of
well-defined physical moves - freedom of conflicts is guaranteed
- when AGVs less than 4n2, solution might not be
optimal - since AGVs are sparse, shortest path will also
be conflict free
421) Algorithms for General Path Topology 2) Path
Optimization 3) Algorithms for Specific Path
Topologies 4) Dedicated Scheduling Algorithms
43Dedicated Scheduling Algorithms
- considers the scheduling of AGVs jobs without
considering the
routing process - Akturk and Yilmaz, 1996
- micro-opportunistic scheduling algorithm (MOSA)
- schedule vehicles jobs in a decision-making
hierarchy - based on mixed-integer programming
- critical jobs travel time of unloaded vehicles
are considered
simultaneously - similar to time constrained vehicle routing
problem (TCVRP) - min. the deviation of the time windows,
polynomially solvable - applicable for systems with small number of jobs
vehicles
44Dedicated Scheduling Algorithms
- Kim and Bae, 1999
- scheduling of AGVs for multiple
container-cranes - minimize the delay of loading/unloading
operations - AGV routing not taken into consideration
- congestion or collusions are possible
45Future Directions
- Development of new scheduling and routing
algorithms
for specific path topologies - have lower computational complexity
- more efficient algorithms can be developed by
investigating
specific
characteristics of topologies - most of the applications have path networks that
can be put in
a specific path topology - Algorithms with provable qualities freedom of
conflicts
46Concluding Remarks
- Latest issues of research
- automated driving of vehicles
- intelligentization of vehicles
- intelligent navigation mechanisms
- robot vision
- image processing
- information fusion
- Problems of scheduling routing will not
disappear
47QUESTIONSANSWERS