AI Dispatch Decision Framework: Stochastic vs. Deterministic Scheduling — 12 FTF Points vs. 87% On-Time Target

This guide delivers the dispatch decision framework that justifies stochastic scheduling only when paired-pilot 95% lower-bound on-time clears 87% and first-time-fix loss stays at or below 12 points.

Otherwise deterministic scheduling remains the audit baseline and only a review-banded hybrid may be considered.

How the Dispatch Mechanism Actually Works

The dispatch scheduler decision reduces to a deterministic-or-stochastic fork, governed by three sequential checks that this section alone codifies. Before any ranking is adopted, the system must verify the first-time-fix outcome, confirm the dispatch mode's reproducibility, and measure the on-time fidelity relative to a paired-pilot baseline. Only when all three thresholds clear does a band earn stochastic ranking; otherwise the audit defaults to deterministic scheduling with a potential review-band fallback. This structure ensures that stochastic promotion is earned, not assumed.

A first-time-fix, or FTF point, is defined strictly here as a job closed at the first visit with no repeat truck roll. The count requires the same job ID, the same physical visit, and the absence of any same-cause return inside the locally audited window. This narrow definition excludes repeat dispatches and ensures that FTF loss is measured only against genuine single-visit resolutions. Because FTF points are the unit of loss comparison, they anchor the entire decision rule.

Deterministic dispatch applies a fixed priority or ranking rule and returns the same assignment for every identical input tuple, guaranteeing reproducibility across runs. Stochastic dispatch, by contrast, ranks candidates by expected cost and on-time distribution and can yield different assignments when the random seed, epsilon value, annealing schedule, candidate set, or code version changes. These mechanical differences are precisely why the three-check order exists: they produce divergent job-level outcomes that must be quantified before a band can be promoted. This section alone maps how seed logs and epsilon decay influence the stochastic path.

To apply this rule, operators run deterministic and stochastic dispatch on the same dispatch stream in lockstep, record the lower-bound on-time and FTF loss for each job pair, and compute review cost plus delay delta for comparison with the split-cost alternative. The lockstep comparison holds stream variance constant because both modes see the same job arrivals, service windows, and customer geometries. If all three conditions clear—lower-bound on-time at least 87%, FTF loss at most 12 points, and review cost plus delay delta below split cost—the band transitions to stochastic ranking; if any condition fails, deterministic dispatch remains for that band and the review-band fallback may be considered.

Evidence: What Three Sources Support

Evidence for the stochastic dispatch scheduler is drawn from four publications named in the grounding: a Baeldung tutorial on deterministic-stochastic optimization, the TUM edge-detection study, an arXiv preprint on a deterministic implementation of stochastic annealing, and a ResearchGate article on stochastic computation. None of these sources provide field-service first-time-fix or on-time performance measurements, so those performance figures must be treated as local checks rather than inherited benchmarks. Their usefulness is methodological; verify peer-review status and applicability before relying on any citation for dispatch audit requirements.

Cavalcanti et al. report that stochastic edge‑detection circuits achieve an RMSE up to one order of magnitude lower than deterministic circuits while the mean absolute error remains comparable. This result is presented only as a variance‑sensitivity test; it does not imply that stochastic dispatch will improve on‑time delivery or reduce first‑time‑fix loss in the dispatch context. These findings underscore the importance of variance testing before adopting stochastic scheduling.

The arXiv deterministic‑implementation paper specifies that annealing of the randomness parameter proceeds to a value of 0.01 during the first million frames, after which it stays constant, and the authors make the code repository publicly available. Consequently, 0.01 and the first‑million‑frame interval serve as concrete audit fields for the epsilon schedule and for verifying the archived implementation.

The five cost fields under consideration are dispatch execution cost, review labor cost, delay penalty cost, split processing cost, and FTF rework cost. Review cost is computed as manual review minutes multiplied by the loaded review rate; delay delta is computed as delay minutes multiplied by the loaded delay rate, and the two are summed for comparison against split processing cost. No numeric values are supplied for these fields in the available sources literature.

Together, these sources establish the reproducibility and variance checks required to evaluate whether the stochastic ranking band satisfies the required on‑time and first‑time‑fix criteria and confirms that the hybrid band is the default winner only when the defined conditions hold.

Frequently Asked Questions

What is the minimum lower-bound on-time percentage required to justify stochastic ranking over the deterministic baseline?

The lower-bound on-time must be at least 87% to justify stochastic ranking over the deterministic baseline.

What is the maximum allowable first-time-fix loss in points for stochastic dispatch to be adopted?

First-time-fix loss must stay at or below 12 points; otherwise deterministic remains the audit baseline.

Under what condition is deterministic scheduling the default audit baseline?

Deterministic scheduling is the default audit baseline when lower-bound on-time falls below 87% or first-time-fix loss exceeds 12 points.

What review cost condition must be met for stochastic ranking adoption?

Stochastic ranking is adopted only if review cost permits, alongside the 87% and 12-point thresholds.

What is the paired-pilot 95% lower-bound on-time threshold mentioned in the framework?

The paired-pilot 95% lower-bound on-time must meet the 87% target threshold for stochastic dispatch to clear 87% on-time performance.

When is a review-banded hybrid considered instead of deterministic scheduling?

Only a review-banded hybrid may be considered when conditions for full stochastic scheduling are unmet, but deterministic remains the required baseline.

Quick answers

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