Reasoning & math
AuraScore 79/100

Last-Mile Dispatch Feasibility and Window Spec

Specify mathematical formulas for route density, service time limits, and delivery time-window feasibility.

Use this template when designing deterministic route-feasibility checks for urban multi-stop delivery dispatches. It structures the core algebraic and logical conditions required to validate route viability.

Template

Role: Lead Routing Algorithms and Logistics Systems Architect

Context

  • Delivery network: {{carrier_network}}
  • Urban delivery zone: {{delivery_zone_profile}}
  • Scheduled drop density: {{daily_stop_density}}
  • Average stem distance from hub: {{average_stem_distance_km}}
  • Traffic delay factor: {{traffic_congestion_multiplier}}
  • Maximum driver shift duration: {{driver_shift_limit_hours}}

Task

Produce an urban delivery feasibility specification containing mathematical models to validate route viability, stop-density feasibility, and time-window compliance for {{carrier_network}} in {{delivery_zone_profile}}.

Method

  1. Formulate the total route transit time equation including stem distance via {{average_stem_distance_km}} and inter-stop travel time.
  2. Incorporate {{traffic_congestion_multiplier}} as a non-linear coefficient applied across dynamic peak delivery intervals.
  3. Model on-site stop service time as a function of drop density using {{daily_stop_density}}.
  4. Formulate the cumulative shift duration equation and enforce the boundary condition bounded by {{driver_shift_limit_hours}}.
  5. Define the mathematical feasibility score ($0.0 \le S \le 1.0$) balancing total drops against strict delivery time windows.
  6. Formulate the time-window penalty penalty function for early arrival wait times and late delivery violations.
  7. Specify the exact mathematical threshold criteria that automatically flags a planned route as infeasible.

Constraints

  • All time calculations MUST be standard minute/hour units with consistent velocity terms (km/h).
  • The feasibility criteria MUST NOT allow total route duration to exceed {{driver_shift_limit_hours}} under any congestion scenario.
  • You MUST explicitly include dwell time per package distinct from vehicle transit time.
  • Avoid heuristic pseudo-code; formulate clear algebraic equations and boolean acceptance rules.

Output format

  • Section 1: Route Duration & Transit Time Equations (stem time, inter-stop transit, traffic adjusted)
  • Section 2: Shift Bounding & Feasibility Logic (drop capacity formulas, boundary constraints)
  • Section 3: Time-Window Violation Functions (cost equations for delays and idle waits)
  • Total length: 450-700 words.

Self-review

  • Confirm stem distance calculations properly account for both outbound and return journeys.
  • Verify that the shift limit constraint creates an impossible-to-dispatch boundary when violated.
  • Check that all variable terms are clearly defined with their respective metric units.
AuraScore breakdown
79/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

research-analysis
research-reasoning-math
transport-logistics
last-mile
route-optimization
dispatch-math