Tutorial: How to Optimize Preferential Logic with ALICE

Here is a clickable tutorial for the trial project Hard Logic Vs. Preferential Logic Explained in 2D. 


1. This tutorial explains the difference between hard logic and preferential logic and provides an example of the benefits of optimizing preferential logic with ALICE

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2. This schedule solution includes all hard logic ties (FS Precedence) between all activiteis/elements in the schedule and only 1 of each crew type available.

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3. Select the fastest solution and check the box to compare multiple solutions

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4. Tap compare solutions

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5. Metrics show you the differences in duration, cost, and average crew utilization.

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6. Parameters show the available resources and the amount used by ALICE in the selected solutions.

Note: Even with infinite resources available ALICE is smart enough to calculate that only 1 is required based on the over-constrained schedule setup.

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7. Select Detailed comparison for a Gantt overlay of the scenarios

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8. In detailed comparison you can see that the precedence ties (hard logic) is fixed and ALICE can't explore alternative sequences. This is how constraints are most commonly modeled in CPM tools like P6 or MS Project.

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9. In detailed comparison you can see that the precedence ties (hard logic) is fixed and ALICE can't explore alternative sequences. This is how constraints are most commonly modeled in CPM tools like P6 or MS Project.

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10. Click here to reverse the Primary and Secondary (yellow bars) schedule views.

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11. Click solutions to go back to the explore page

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12. Now select plan to see how the logic looks in the planning setup.

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13. Click Open on the plan name
Hard Logic For All (typical approach in P6 with precedence ties only)

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14. Here you can see a 2D Logic Diagram view of the project setup. The arrows are supports (FS relationships) between the elements or work packages

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15. This is how CPM schedules are commonly built because precedence is used to model resource and area constraints. This over constraining of the plan is not required in ALICE
Overconstrained schedules are fragile and miss big opportunities.

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15b. Drop

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16. This is an example of a plan that has introduced variability and let ALICE optimize preferential constraints for zones of work packages. ALICE will now dynamically allocate resources based on availability and criticality.

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17. This is a dynamic setup where preferential logic between elements has been removed to enhance optimization.

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18. Preferential logic ties between Paving zones were removed since this is not a hard constraint on the job (example).

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19. Click Go to solutions to simulate the schedule impact of these changes

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20. Scroll and click highlight

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21. Click Isolate

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22. Click highlight to isolate the hard logic and preferential logic with 1 crew of each type available.

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23. comparing the solutions you can see that there is no difference in duration or cost because the available resources have not changed and 1 of each crew limits any overlaps.

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24. Click highlight and isolate for 2 of each crew type. Removing preferential logic ties gained

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25. Click highlight

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26. Click highlight

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27. Click highlight

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28. Click highlight to see the saturated solutions

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29. Click highlight

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30. Scroll down and click on

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31. Click highlight to select this solution for comparison

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32. Scroll up and click highlight

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33. Click on

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34. Click Compare Solutions

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35. Scroll and click Detailed comparison

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36. Click highlight to filter the Gantt view

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37. Click Paving Crew

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38. Click Done

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39. In this comparison view you can see the solution with preferential logic removed ALICE was able to dynamically allocate paving crews and sequence based on resource availability.

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40. Scroll and that's it. You're done.

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** Best experienced in Full Screen (click the icon in the top right corner before you begin) **


Next step

This article and tutorial explain the differences between hard logic and preferential logic with examples of how to remove preferential logic in your schedule in order to let ALICE dynamically re-sequence and allocate resources.

1. Hard Logic:

Definition: This logic refers to mandatory relationships between activities that are inherent to the work being performed. These are constraints that can't be violated without affecting the project outcome or risking safety, quality, contractual requirements or other critical factors.

2. Soft / Preferential Logic:

Definition: This logic refers to relationships that are based on best practices, historical precedence, or other non-mandatory constraints. These relationships can potentially be adjusted or re-ordered based on resources, risks, or other project conditions.


Using Hard Logic & Soft Logic to build a well-balanced schedules 

In planning and scheduling, ignoring hard logic can lead to technical errors, increased risks, and potential project failures. Over-relying on preferential logic can lead to inefficiencies and limit the schedule's flexibility. Scheduling mandates a harmonious blend of both logics. Hard logic ensures a technically correct project sequence, safeguarding quality and safety. Preferential logic offers scheduling flexibility, paving the way for resource optimization, risk reduction, and potential time/cost savings.


Automate fine-tuning of preferential logic with ALICE for antifragile scheduling 

While traditional CPM solutions rely on precedence to model hard and preferential logic constraints, modern tools like ALICE introduce innovative functionalities. For those unfamiliar, ALICE is a generative scheduling platform. Within ALICE, hard logic is depicted by 'supports'. In contrast, preferential logic is dynamic, employing advanced features like grouping, parametric recipes, and resource saturation.

Generative scheduling with ALICE permits planners to centralize their efforts on defining hard logic using support constraints. ALICE then crafts a myriad of sequences and resource allocations, adhering to hard constraints while optimizing the soft. This methodology equips planners to rapidly pinpoint the optimal strategy, harnessing intelligent algorithms to swiftly evaluate various options. Thus, project teams are better positioned to adapt to shifts, automating the fine-tuning of preferential constraints to unlock efficiency.


Hard Logic Soft / Preferential Logic
Install formwork and rebar before pouring Pour zone 1, then 2, then 3
Excavate then install drainage Close down 2 lanes instead of 3
Lay foundation before erecting walls Start with the west wing before the east
Electric wiring before turning on the power Work two hours of overtime on Monday 
Roofing before interior drywall installation Number of crews installing drywall in an available floor 


Some key differences:

  • Hard logic must be satisfied - preferential logic should be satisfied if possible.
  • Hard logic limits options - preferential logic guides selection between multiple options.
  • Violating hard logic makes a schedule invalid - violating preferential logic just makes the schedule less optimal.
  • Hard logic is black and white - preferential logic allows for shades of gray and balancing multiple preferences.
  • Hard logic focuses on constraints - preferential logic focuses on optimization and goals.


  • There can also be shades of gray between hard and preferential logic.
  • In ALICE supports are used to model hard logic, however, if you assign multiple next supports - this enables ALICE to explore various sequences of preferential logic and recommend the optimal solution based on your objectives 


Common Types of preferential logic to remove in a schedule in order from lowest risk to highest risk:


Typical Workflow Logic: Reflects standard sequences or work practices that are not mandatory constraints. For example, installing material from east to west. Changes unlikely to present technical issues or risks. Opportunity to optimize workflows.


Crew Availability Logic: Sequencing is driven by assumed crew movements between zones rather than technical constraints. For example, following a strip forms activity with the next zone's formwork may be based on assumed crew availability. Some risk of resource contention, but opportunities to optimize.

Planning Logic: Front-end planning, procurement, or submittal activities tied to other activities based on preference rather than technical dependency. For example, tying shop drawing approval to installation.


Milestone Logic: Activities tied to interim milestone dates that are arbitrary targets rather than true technical dependencies. Meeting a milestone date may drive preferential sequencing. Low risk if dates are reasonable targets.


Assumed Safety Logic: Sequencing activities in a certain order purely for assumed safety reasons that are not actual requirements. For example, completely finishing one zone before starting earthwork in the next. Changes could introduce safety risks if not properly validated. Humans should verify new sequences are safe.


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