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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.
Examples:
| 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.
Notes
- 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.