You 'll want incremental score calculation (with delta's) for your "end times".
http://docs.jboss.org/drools/release/5.4.0.Final/drools-planner-docs/html_single/index.html#incrementalScoreCalculation

So that naturally puts the calculation of those end times in the scoreDRL (or IncrementalJavaCalculator if you're not using drools). Whether or not that endTime should be a property on the model (at least the model that Planner works with), is an open design question. If it isn't, you can use insertLogicals in DRL, like I did in nurserostering to calculate the number of sequential weekends being worked etc. If it is a property on your model, either the DRL must first "correct it" (with higher salience rules for example), or custom moves must "correct it" as they are being done (which is very hard as it entails constraints functionality).

As for the cloning: it's quite simple:
Either the model's entity contains the endTime property, then clone it.
If it doesn't, then there's nothing to clone.
I don't see any problems related to the cloning.

Op 18-08-12 01:53, Josef Bajada schreef:
Hi Geoffrey,

Following your advice and after gaining some more understanding of planner, I think approaching the problem as a chain of tasks one of the other makes sense. It would have some 'wait' time between tasks where the end time of the previous task is smaller than the minimum time the task has to wait after its dependency (which could be different from the previous task).

I've noticed that in most examples (TSP and VRP), there is some separation between the model and the planning entity that is being moved around in the chain, which also makes sense. (For instance in TSP, Visit is the planning entity while City is the data entity). When the planning entity gets cloned, the data entity gets assigned to the clone.

I am concerned however, that with my dependency between tasks and their end times (which are as such a property of the planning entity not the data entity) I won't be able to model them in this way. (For a task to know whether it has violated its hard constraint it needs to get access to the end time of its dependency, which is in the planning entity). My concern is that I might end up with a whole mess when it comes to the cloning of tasks. I am also concerned about the performance of computing the end time of each node recursively based on its previous task and dependent tasks.

What is the best approach in this case?

thanks,

Josef



On 25 July 2012 08:30, Geoffrey De Smet <ge0ffrey.s...@gmail.com <mailto:ge0ffrey.s...@gmail.com>> wrote:


    Op 24-07-12 23:14, Josef Bajada schreef:
    Hi Geoffrey,

    Thanks for your reply.

    > Does it make sense to wait longer than 7 mins after task A
    (presuming no other task forces occupies the user at that time)?
    > Put differently: Can we say that the starting time of B =
    Math.max((endTime of task before B), (endTime of task A + 7
    minutes))?
    > If we can say that, it's pointless to investigate the solutions
    where task B starts 8 minutes after task A and the user doing no
    task that last minute.

    Yes, the starting time of B = Math.max((endTime of task before
    B), (endTime of task A + 7mins)) as long as it is smaller than
    (endTime of task A + 8mins).
    Yes, it is pointless to investigate the solutions where task B
    starts 8 minutes after task A and the user doing no task that
    last minute.
    The 8 minute is just a constraint that the task in between tasks
    A and B cannot take longer than 7:59s.

    I am thinking that maybe instead of using time itself as the
    planning variable, we would use time just to determine the Hard
    and Soft scores.
    So if Task B is scheduled after Task A + 8mins by the solver,
    then it inflicts on the hard score. Similarly if Task B is
    scheduled before Task A + 7 mins.
    Does my reasoning make sense in any way?
    Yes, but personally, I 'd design it differently (although I have
    no proof that my way would be better), like this:
    "Task B is scheduled after Task A + 8mins by the solver" => make
    this a hard constraint
    "Task B is scheduled before Task A + 7 mins" => make this a
    build-in hard constraint (= not a constraint in the scoreDRL or
    ScoreCalculator, but by design, see manual).
    Each Task is assigned to a previousTaskOrPerson (and this variable
    is chained). It does not know it's startingTime directly.
    The scoreDRL or ScoreCalculator calculates the startingTime of a
    Task dynamically, by applying this logic:
      starting time of B = Math.max((endTime of previousTaskOrPerson
    of B), (endTime of task A + 7mins))
    Note: "Chained=true" guarantees that there are no cycles of Tasks
    and that no Tasks exists with a previousTaskOrPerson == null.
    Note: "(endTime of task A + 7mins)" is not hard coded in the score
    function: you won't find "7" or "A" in there.



    thanks,
    Josef



    On 24 July 2012 20:46, Geoffrey De Smet <ge0ffrey.s...@gmail.com
    <mailto:ge0ffrey.s...@gmail.com>> wrote:


        Op 23-07-12 16 <tel:23-07-12%2016>:26, Josef Bajada schreef:
        Hi Geoffrey,

        Well I want to leave 'space' between tasks in the situations
        where there are hard constraints that require me to put this
        space.
        This makes the chaining technique harder to model, but I
        wouldn't write it off yet.


        As a simple example:

        Task A: Put pasta in boiling water (duration 40 seconds)
        Task B: Take pasta out of boiling water (duration 50
        seconds, cannot start before 7 mins after Task A finishes,
        cannot start after 8 mins after Task A finishes)
        Does it make sense to wait longer than 7 mins after task A
        (presuming no other task forces occupies the user at that time)?
        Put differently: Can we say that the starting time of B =
        Math.max((endTime of task before B), (endTime of task A + 7
        minutes))?
        If we can say that, it's pointless to investigate the
        solutions where task B starts 8 minutes after task A and the
        user doing no task that last minute.
        If we can say that, then chaining can calculate the the
        starting time of a task on the fly differently.

        Task C: Chop vegetables (duration 2 minutes).

        This will evidently leave some gaps. The ideal result from
        the solver should be:

        Task A: at time 0 (ends at 40s)
        Task C: at time 41s (ends at 2:41)
        Task B: at time 7:40

        There is a gap between C and B which is OK.

        If another Task is added to the story:
        Task D: Prepare sauce (duration 7 minutes)

        I would want the following result:

        Task A: at time 0 (ends at 40s)
        Task D: at time 41s (ends 7:41s)
        Task B: at time 8:42s (ends 9:32s)
        Task C: at time 9:33s (ends 11:33s)

        Task C can actually take place before Task A too.

        I still need to read and understand the chaining
        functionality properly. Do you think it would allow me to
        achieve the above?

        I don't know.
        But using continuous variables in a search problem such as
        this that smells discrete with discrete constraints (A must
        start before B, ...), could blow up the search space
        unnecessarily.

        If you want to look into using continuous variables: the
        support for it is limited currently.
        you can reuse the Drools Planner metaheuristic algorithms
        (including termination, score, ...), but there's no decent
        generic move factory support for continuous variables yet.
        So you 'll have to write a custom MoveFactory that creates a
        limited subset of moves.
        Also, construction heuristics can't handle continuous
        variables yet, so you 'll have to write a custom
        SolutionIntializer.
        There are examples with a custom MoveFactory and a custom
        SolutionIntializer where you can copy paste from, but none
        with continuous variables at the moment.

        thanks,

        Josef



        On 22 July 2012 20:05, Geoffrey De Smet
        <ge0ffrey.s...@gmail.com <mailto:ge0ffrey.s...@gmail.com>>
        wrote:

            Presuming that you don't want to leave space between
            tasks, you can design your model differently by using
            the "chained" functionality:
            it will be far more efficient and the planning variable
            won't be continuous.

            Let's presume you're scheduling Tasks to Persons.

            @PlanningEntity
            class Task implements TaskOrPerson {

                ...

                @PlanningVariable(chained = true)
                @ValueRanges({
                        @ValueRange(type =
            ValueRangeType.FROM_SOLUTION_PROPERTY, solutionProperty
            = "taskList"),
                        @ValueRange(type =
            ValueRangeType.FROM_SOLUTION_PROPERTY, solutionProperty
            = "personList",
            excludeUninitializedPlanningEntity = true)})
                public TaskOrPerson getPreviousTaskOrPerson() {
                    return previousTaskOrPerson;
                }

                public int getDuration() {
                    return duration;
                }

                public int getStartingTime() {
                      int startingTime = 0;
                      TaskOrPerson taskOrPerson =
            getPreviousTaskOrPerson();
                      while (taskOrPerson instanceof Task) { //
            Every chain is guarantee to end up with an anchor (= Person)
                            startingTime += ((Task)
            taskOrPerson).getDuration();
                            taskOrPerson = ((Task)
            taskOrPerson).getPreviousTaskOrPerson()
                      }
                      return startingTime;
                }

            }

            class Person implements TaskOrPerson {

            }

            For a good example, take a look at the VehicleRouting
            example.
            For more info about chaining, in the manual see section
            4.3.4.2.6. Chained
            
http://docs.jboss.org/drools/release/5.4.0.Final/drools-planner-docs/html_single/index.html

            Op 22-07-12 18 <tel:22-07-12%2018>:00, Josef Bajada schreef:
            Hi,

            I am new to Drools and Drools Planner, so apologies if
            I am asking anything obvious.

            My objective is to implement a simple (for now) planner
            which schedules tasks according to 2 main criteria:
            - Their duration (in seconds)
            - Their dependencies on other tasks (e.g. Hard
            Constraint that Task B has to start between 180 and 200
            seconds after Task A finishes).

            Since there are gaps between dependent tasks as part of
            the hard constraints other tasks can be fitted in
            between dependent tasks.
            So the Solver needs to find the optimal start time for
            each task that satisfies the hard constraints, and in
            the shortest total timeline possible to complete all
            tasks (soft constraint).

            The main problem I am finding is that this start time,
            which is essentially the planning variable is a
            continuous variable.
            Chapter 4 of the Drools documentation mentions very
            briefly (Section 4.3.4.1)  that planning variables can
            be continuous, but there does not seem to be any more
            details about how to achieve this.

            Even if the planning variable was discrete (say bins of
            5 second intervals), there is no upper bound as such.

            How is it best to handle such planning variables in
            Drools Planner?

            thanks,
            josef




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-- With kind regards,
            Geoffrey De Smet


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-- With kind regards,
        Geoffrey De Smet


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-- With kind regards,
    Geoffrey De Smet


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