Transcript Slide 1

The Axxom Case Study
state of the art
Ed Brinksma
joint work with
Gerd Behrmann
Martijn Hendriks
Angelika Mader
AMETIST
Review Meeting, Brussels, 13
November 2005
Contents
 case study description
 information transfer
 modelling
 heuristics
 extended case study
 results
 evaluation & current work
AMETIST
Review Meeting, Brussels, 13 November 2005
Case Study Description
 lacquer production scheduling
 3 recipes
 for uni/metallic/bronce lacquers
 use of resources, processing times,timing
 29 (73, 219) orders:
 start time, due date, recipe
 extensions:
 delay costs, storage costs, setup costs
 weekends, nights
AMETIST
Review Meeting, Brussels, 13 November 2005
Information Transfer
Stumbling blocks:
 interpretation of terminology
 creation of a dictionary
 implicit knowledge
 late modification of models
 biased model description
 based on Orion-pi features
 non-standard notation
AMETIST
Review Meeting, Brussels, 13 November 2005
An Axxom Recipe
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AMETIST
Review Meeting, Brussels, 13 November 2005
The recipes
in an alternative
representation
AMETIST
Review Meeting, Brussels, 13 November 2005
A Basic Processing Step
time<=processing_time
resource>0
resource -time:=0
time==processing_time
resource++
 timed automaton with 3 locations:
 claiming a resource
 processing
 releasing a resource
 template with parameter for processing_time
 combined into recipies and composed with models for resources
AMETIST
Review Meeting, Brussels, 13 November 2005
Scheduling Synthesis
 use real-time model checker (Uppaal) to
determine the reachability of states where
all orders have been processed in time
 schedules can be extracted directly from
witness traces to such states
 problem: state space explosion
 use heuristics to prune search tree
AMETIST
Review Meeting, Brussels, 13 November 2005
Heuristics
We distinguish:
 “nice” heuristics
do not remove best remaining schedule
 “cut-and-pray” heuristics
may remove best remaining schedule
AMETIST
Review Meeting, Brussels, 13 November 2005
Nice Heuristics
 non-overtaking
orders of the same recipe cannot overtake
each other
 non-laziness
a process that needs an available resource
will not waste time if its is not claimed by
others (a.k.a. active scheduling)
AMETIST
Review Meeting, Brussels, 13 November 2005
A Non-Lazy Processing Step
time<processing_time
resource==0
urgent!
resource>0
time:=0
time<=processing_time
resource>0
urgent!
resource -time:=0
AMETIST
time==processing_time
resource++
Review Meeting, Brussels, 13 November 2005
Cut-and-Pray Heuristics
 greediness
a process that needs an available resource
will claim this resource immediately
 reducing active orders
the number of concurrent orders is
restricted (number of critical resources
can give an indication)
AMETIST
Review Meeting, Brussels, 13 November 2005
Experimental Results
#jobs
heuristic
max.
orders
29
29
73
nl
nl, no
-
term.
time
1s
-
73
nl, no
3
7s
219
g, no
4
8s
uses clock optimization &
optimized successor
calculation
AMETIST
Review Meeting, Brussels, 13 November 2005
Extending the Case Study
1. performance and availability factors
if a resource has an average availability factor f,
its processing time is multiplied by 1/f.
2. storage, delay and setup costs,
working hours
penalties for delivering orders too early, or too
late; costs for cleaning filling stations; work in
shifts, no work over weekends.
AMETIST
Review Meeting, Brussels, 13 November 2005
Results
Availability Factors
#jobs
heuristic
max.
orders
29
nl, no
-
1s
29
g
-
<1 s
73
nl, no
-
-
73
nl, no
4
3s
73
g, no
4
3s
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Review Meeting, Brussels, 13 November 2005
term.
time
Storage, Delay,
and Setup Costs
 use cost-extended Uppaal CORA
 cost optimization problem
 delaying earliest starting time heuristic
(cut-and-pray)
time<=processing_time
cost’==late[id]*dcf
cost’==late[id]*dcf
resource>0
resource -time:=0
AMETIST
cost’==late[id]*dcf
time==processing_time
resource++
Review Meeting, Brussels, 13 November 2005
Working Hours
Taken into account through an extra
automaton that calculates the effective
processing time “online”.
This increases the size of the model
considerably
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Review Meeting, Brussels, 13 November 2005
Results Extended Case
heuristic
max.
orders
min. cost
found in 60 s
-
es, no, nl
-
530,771
29
-
29
avail.
29
avail.
es, no, competitive
g
with
es, no, nl
Orion-pi
es, no, g results-
29
expl.
#jobs
work
hrs
29
AMETIST
no
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Review Meeting, Brussels, 13 November 2005
647,410
1,714,875
2,263,496
192,881,129
Evaluation
 successful extension of core scheduling problem to
73 and 219 orders
all results obtained < 10 s (PC 512MB, 1GHz)
 generic patterns for processing steps, resources,
and heuristics
 first results for inclusion of costs and working hours
results competitive with Orion-pi
 information transfer was a non-trivial problem
AMETIST
Review Meeting, Brussels, 13 November 2005
Current Work
 scaling up the core problem to O(103) orders
 seems feasible with active orders heuristic
 relation between long-term feasibility and
short-term planning schedules
 availability and performance factors are
approximative
 irrelevance of cost factors and working hours for
long planning periods
 searching for schedules in reverse time
 minimize storage and delay costs
AMETIST
Review Meeting, Brussels, 13 November 2005