[jboss-jira] [JBoss JIRA] Updated: (JBRULES-2900) Planner optimization algorithms should include Jacoby and Gauss-Seidel iterations
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https://issues.jboss.org/browse/JBRULES-2900?page=com.atlassian.jira.plug...
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Geoffrey De Smet updated JBRULES-2900:
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Summary: Planner optimization algorithms should include Jacoby and Gauss-Seidel
iterations (was: Consider concurrency tasks optimization (both Jacoby and Gauss-Seidel
iterations))
Note: concurrency task optimization (machine queue planning) is a good use case to
implement with vanilla Drools Planner with Tabu search/Simulate annealing.
Machine queue planning suffers from additional constraints which are hard to implement as
mathematical equations, such as:
- machine X can not handle type Y jobs
- prefer newer machine A over older machine B for type C jobs to lower the risk of the
quality being insufficient, unless machine A is full
- heavier products should be scheduled to machines closer to the exit
Planner optimization algorithms should include Jacoby and
Gauss-Seidel iterations
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Key: JBRULES-2900
URL: https://issues.jboss.org/browse/JBRULES-2900
Project: Drools
Issue Type: Feature Request
Security Level: Public(Everyone can see)
Components: drools-planner
Affects Versions: FUTURE
Reporter: Michał Warecki
Assignee: Geoffrey De Smet
Priority: Minor
Fix For: Out of scope
Will be great to support concurrency tasks optimization.
In example we have 3 tasks A, B, C and objective function 2A^2 + A*B + B^2 + AC. With
Gauss-Saidel iteration (where task B in time+2 depends on A in time+1 and C in time+2
depends on A in time+1) we can execute tasks A,B,C in order: A and BC cocurrently, so in 2
iterations. Without optimization tasks will be executed in 3 iterations (A , B, C).
We should support Jocoby iteration as well where tasks B and C does not depend on A in
previous iteration.
This can be done with Gradient Method.
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