Decision Optimization

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How to maintain the presence of group of Interval variables in scheduling problem using Cplex Python?

  • 1.  How to maintain the presence of group of Interval variables in scheduling problem using Cplex Python?

    Posted Thu September 22, 2022 04:33 PM
    Edited by System Fri January 20, 2023 04:23 PM
    Hello,

    So basically I have a scheduling problem where all tasks (interval variables) are optional and it belongs to different groups. Like as an house building problem, but here I have different tasks (not same at all) for different houses and I want to model that it fully completes as many houses as possible by finishing all tasks for those houses. I am also checking for the resource capacity that it won't exceed the given capacity. (So main goal is to fully complete the houses as much as possible and if capacity permits also select some tasks to use the remaining capacity, even if last house can't be complete )

    So here I'm trying to count the presence_of() tasks (Model picks in solution) from perticular house and then check if those are all tasks for a house to be finish completely, and then try to maximize the number of completed houses. But it's not working and giving me an error that "CPO expression can not be used as boolean". I would really appreciate any help to make it work! Thank you!


    ------------------------------
    Patel
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    #DecisionOptimization


  • 2.  RE: How to maintain the presence of group of Interval variables in scheduling problem using Cplex Python?

    Posted Thu September 22, 2022 05:10 PM
    Edited by System Fri January 20, 2023 04:42 PM
    Dear Patel,

    Could you please provide a short model that shows the error you describe?
    Thank you in advance,

    Edit: I suggest that you have a look at the house_building example that seems to  match what  you want to do:
    docplex-examples/house_building.py at master · IBMDecisionOptimization/docplex-examples
    GitHub remove preview
    docplex-examples/house_building.py at master · IBMDecisionOptimization/docplex-examples
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    ------------------------------
    Renaud Dumeur
    ------------------------------

    Original Message


  • 3.  RE: How to maintain the presence of group of Interval variables in scheduling problem using Cplex Python?

    Posted Fri September 23, 2022 04:59 PM
    Edited by System Fri January 20, 2023 04:13 PM
    Hello @Renaud Dumeur,
    Thank you for your prompt reply. I had look into the all examples out there for CP model. But here in my scheduling problem, what's the difference than the ​house_building.py example is I have list of Tasks unlike same task list for all houses. It's different tasks for different house. Like Tasks = {T1H1, T2H1, T3H2, T4H3, ... }. So aim (Objective) is to maximize the count of Houses that can be fully completed (100% completed houses from solution).

    I tried below code for this, which gives me the error "CpoException: CPO expression can not be used as Boolean."

    mdl0.add(cp.maximize(sum ( 1
                for H in Houses
     if
                sum((cp.presence_of(dictIntrvalVarsTasks[T]) * 1) for T in Tasks) ==
    dfAllTasks.loc[dfAllTasks[    'House'] == H, 'TaskName'].count()
              )))

    Here, in the code first I'm trying to get sum of houses which can be completed 100% using the condition (
    if
                sum((cp.presence_of(dictIntrvalVarsTasks[T]) * 1) for T in Tasks) == dfAllTasks.loc[dfAllTasks['House'] == H, 'TaskName'].count()
    ), and check that if sum of present tasks in solution are equal to the total tasks for the house? If so that means all tasks for that house is completed and so the house. And maximize that sum.

    Hope I explained it enough, but please let me know if there is any question. Thanks a lot in advance. Hope you or somebody could help me with this! :)

    ------------------------------
    Patel
    ------------------------------

    Original Message


  • 4.  RE: How to maintain the presence of group of Interval variables in scheduling problem using Cplex Python?

    Posted Sat September 24, 2022 09:13 AM
    Dear Patel,

    You are trying to iterate on your data and use the solver state (accessed via cp.presence_of) in your comprehension. 
    It cannot work since, when your comprehension is executed, your solver hasn't started yet! You are still building the model.
    To maximize the number of houses that must be fully completed you can:
    - define a completion expression for each house:
       house_completion = [ cp.sum(cp.presence_of(dictIntrvalVarsTasks[T]) for T in HouseTasks[h])) for h in Houses ]
    - a 100% completed expression relying on house_completion:
    house_fully_completed = [ (house_completion[h] == len(HouseTasks[h])) for h in Houses ]
    - maximize cp.sum(house_fully_completed)
    I hope this helps,
    Cheers,

    ------------------------------
    Renaud Dumeur
    ------------------------------

    Original Message