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I don't have the time budget to do a full code review for a
community question,<br>
but here are my initial thoughts:<br>
<br>
<br>
A) Is your average calculation count per second above 5000?<br>
If not, figure out which score rules are slowing you down.<br>
<br>
<br>
B) Your assessment of "Concept with timeslots has to many possible
order positions." might be correct.<br>
<br>
I've seen before on job shop scheduling problems,<br>
that having second grained accuracy on starting time, in cases with
days/weeks of running time,<br>
where each job (=order) takes minutes - is inefficient in a
straightforward model, currently.<br>
Specifically because the constraints want the jobs to be pasted
after each other.<br>
<br>
Here are (parts of) a solution for B):<br>
<br>
1) Use a smarter (more complex model) that leaves less pointless
combinations.<br>
Some idea's:<br>
- Look at the Project Job Scheduling example's source code.<br>
<a class="moz-txt-link-freetext" href="http://www.youtube.com/watch?v=_2zweB9JD7c">http://www.youtube.com/watch?v=_2zweB9JD7c</a><br>
If orders have dependencies on each other, this works well.<br>
- Look at Vehicle Routing with Time windows. Maybe this model works
for you:<br>
Each Vehicle = 1 of your machines. Each customer = 1 job.
ArrivalTime = startingOrderTime.<br>
Setup times etc are added automatically in the arrivalTime due to
the VariableListener.<br>
<br>
2) (Future) For OptaPlanner 6.1.0.Beta1 (which is coming soon), we
are working on numeric ValueRanges.<br>
<a class="moz-txt-link-freetext" href="https://issues.jboss.org/browse/PLANNER-160">https://issues.jboss.org/browse/PLANNER-160</a><br>
This way, if a the values are (00:01, 00:02, 00:03, ..., 00:55,
...),<br>
OptaPlanner understands that 00:02 is closer to 00:03 than to 00:55,<br>
and the generic change move selector will support a gaussian
distribution random close to it's current value.<br>
<br>
3) (Future) "CH based metaheuristics" (also called "indirect
metaheuristics" - or by me "feature L").<br>
Too hard to explain now, but research shows this is very promising
for these kind of use cases (a big leap forward).<br>
I am confident I can make it simple to use (despite it's inherit
complexity), hopefully for 6.1.<br>
It does have some drawbacks and limitations (especially if you rely
on a specific types of soft constraints).<br>
<br>
<br>
<div class="moz-cite-prefix">On 20-11-13 17:32, Mohr, Michael wrote:<br>
</div>
<blockquote
cite="mid:061987E4D707A946AE38FB38AB077C9C018D3EEF0BE1@lu-exchange.koehl.eu"
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<p class="MsoNormal"><span lang="EN-US">Hi,<o:p></o:p></span></p>
<p class="MsoNormal" style="margin-bottom:12.0pt"><span
lang="EN-US"><br>
I must find start and end times for orders on different
equipment’s in requirement of a stock.<br>
What can I do better to get faster a solution.<br>
<br>
I read the forum entries but it don't helps.<br>
- Scheduling events with varying durations - corrupted score<br>
- Time Slots vs Time Periods<o:p></o:p></span></p>
<p class="MsoNormal"><b><span style="color:black" lang="EN-US">Graphics</span></b><b><span
lang="EN-US">
<span style="color:black">and detail </span>description
in the pdf. <o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US">Domain model<br>
<br>
@PlanningEntity<br>
EquipmentAllocation has a Equipment<br>
EquipmentAllocation has a Order<br>
EquipmentAllocation has a TimeSlot<br>
------------------------------------------------------<br>
@PlanningVariable<br>
Order<br>
Attribute: quantity<br>
------------------------------------------------------<br>
TimeSlot<br>
Attribute: startTime, endTime, duration, sequenceNumber<br>
------------------------------------------------------<br>
Material<br>
Attribute: stock, minStock, maxStock<br>
------------------------------------------------------<br>
Material Demand has a TimeSlot<br>
Attribute: quantity<br>
------------------------------------------------------<br>
<br>
Conditions:<br>
- Order is executable on each equipment.<br>
- Orders has different sizes.<br>
- Order running time is depending of the material and
the equipment.<br>
- Gaps between orders are possible if there is no
demand.<br>
- Gaps between orders are possible when there is a
equipment setup time.<br>
- Parallel orders with same material on different
equipment’s are possible.<br>
<br>
Target:<br>
- Calculate start and endtims for an order.<br>
- Start and endtime is precisely one minute (maximum
five minutes if runtime is to long).<br>
- Satisfy only the demand of a material.<br>
- Good result in 5 minutes.<br>
- No exceed min or max stock.<br>
<br>
Plan data:<br>
- Plan for 24 hours.<br>
- Plan 35 orders (normal order time is 2 hours).<br>
- Plan 5 demands with different materials (7 orders
per demand).<br>
- Plan 3 equipment’s.<br>
<br>
Problem:<br>
- No result in 5 minutes.<br>
- Concept with timeslots has to many possible order
positions.<br>
- No restrictions are possible to find the best
solution.<br>
<br>
Use a pillar swap to create the possible order positions on
each equipment.<br>
Use a pillar swap to lay the order over a lot of timeslots
on a equipment.<br>
<br>
Example:<br>
- 1 order (with 2 hours)<br>
- 1 equipment<br>
- 24 hours planning time with 1 timeslot per minute<br>
- Possible order positions = 22 * 60 = 1320 (on one
equipment)<br>
- Possible order positions = 1320 * 3 = 3960 (on
three equipment)<br>
- Possible order positions = 3960 * 35 = 138.600 (all
orders on all equipment)<br>
<br>
<br>
rule "Check order not allocate to less."<br>
<br>
when<br>
$f : Order( $quantity : quantity , $m :
material )<br>
<br>
$result : Number( (intValue > 0)
&& ( intValue < $quantity ) )<br>
from accumulate(<br>
EquipmentAllocation( order != null
&& order == $f , $sp : equipment.speedMap ),<br>
sum($sp.get($m))<br>
)<br>
then<br>
int hard = $result.intValue() - $quantity;<br>
scoreHolder.addHardConstraintMatch(kcontext,
hard );<br>
end<br>
<br>
<br>
rule "Check order not allocate to many."<br>
<br>
when<br>
$f : Order( $quantity : quantity , $m :
material )<br>
<br>
$result : Number( (intValue > 0)
&& ( intValue > $quantity ) )<br>
from accumulate(<br>
EquipmentAllocation(order != null
&& order == $f , $map : equipment.orderMap )<br>
sum( $map.get( $f ))<br>
)<br>
then<br>
int hard = $quantity - $result.intValue();<br>
scoreHolder.addHardConstraintMatch(kcontext,
hard );<br>
end<br>
<br>
<br>
rule "Check demand"<br>
<br>
when<br>
$m : Material( $stock : stock )<br>
<br>
$t : TimeSlot( $sequence : sequence )<br>
<br>
$sumDemand : Number( )<br>
from accumulate (<br>
Demand ( timeSlot.sequence <=
$sequence , material == $m , $quantity : quantity )<br>
sum( $quantity )<br>
)<br>
<br>
$sumAllocation : Number( ($stock + intValue
- $sumDemand.intValue()) < 0 )<br>
from accumulate (<br>
EquipmentAllocation( (order != null
&& order.material == $m) , timeSlot.sequence <=
$sequence , $sp : equipment.speedMap),<br>
sum( $sp.get($m) )<br>
)<br>
then<br>
scoreHolder.addHardConstraintMatch(kcontext, -1);<br>
end<br>
<br>
<br>
rule "Check min stock"<br>
<br>
when<br>
$m : Material( $stock : stock , $minStock :
minStock, $maxStock : maxStock )<br>
<br>
$t : TimeSlot( $sequenceT : sequence )<br>
<br>
$sumDemand : Number( )<br>
from accumulate (<br>
Demand ( timeSlot.sequence <=
$sequenceT , material == $m , $quantityDemand : quantity )<br>
sum( $quantityDemand )<br>
)<br>
<br>
$sumAllocation : Number( ($stock +
(intValue) - $sumDemand.intValue()) < $minStock )<br>
from accumulate (<br>
EquipmentAllocation( order != null
, order.material == $m , timeSlot.sequence <= $sequenceT
, $sp : equipment.speedMap ),<br>
sum( $sp.get($m) )<br>
)<br>
then<br>
scoreHolder.addHardConstraintMatch(kcontext, -1);<br>
end<br>
<br>
<br>
rule "Check max stock"<br>
<br>
when<br>
$t : TimeSlot( $sequence : sequence )<br>
<br>
$m : Material( $stock : stock , $maxStock :
maxStock )<br>
<br>
$sumDemand : Number( )<br>
from accumulate (<br>
Demand ( timeSlot.sequence <=
$sequence , material == $m, $quantityDemand : quantity)<br>
sum( $quantityDemand )<br>
)<br>
<br>
$sumAllocation : Number( ($stock + intValue
- $sumDemand.intValue()) > $maxStock )<br>
from accumulate (<br>
EquipmentAllocation( (order != null
&& order.material == $m) , timeSlot.sequence <=
$sequence , $sp : equipment.speedMap ),<br>
sum( $sp.get($m) )<br>
)<br>
then<br>
scoreHolder.addHardConstraintMatch(kcontext, -1);<br>
end</span><span
style="font-family:"Tahoma","sans-serif";color:black"
lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal"><span
style="font-family:"Tahoma","sans-serif";color:black"
lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"
style="mso-margin-top-alt:auto;margin-bottom:12.0pt"><span
style="font-family:"Tahoma","sans-serif";color:black;mso-fareast-language:DE">Gruß<br>
<br>
</span><b><span
style="font-size:12.0pt;font-family:"Tahoma","sans-serif";color:black;mso-fareast-language:DE">Michael
Mohr</span></b><b><span
style="font-size:12.0pt;font-family:"Arial","sans-serif";color:black;mso-fareast-language:DE"> </span></b><span
style="font-size:14.0pt;font-family:"Arial","sans-serif";color:black;mso-fareast-language:DE"><br>
</span><span
style="font-family:"Tahoma","sans-serif";color:black;mso-fareast-language:DE">Software
Engineer
</span><span
style="font-size:12.0pt;font-family:"Arial","sans-serif";color:black;mso-fareast-language:DE"><o:p></o:p></span></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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