Forecasting Engine for Logistics Planning

Regulatory Framework

FMCSA Hours of Service rules (49 CFR Part 395) cap driving and on-duty time for property-carrying commercial motor vehicle operators in the United States: 11 hours of driving within a 14-hour duty window after 10 consecutive hours off, 60/70-hour weekly limits with restart provisions, mandatory 30-minute breaks within the first 8 hours of driving, sleeper-berth split provisions, and adverse-conditions exceptions. The 2017 Electronic Logging Device Mandate requires that compliance be recorded by tamper-resistant ELD hardware that connects to the engine control module and produces auditable RODS (record of duty status) data; FMCSA's compliance reviews and roadside inspections evaluate ELD output directly. Any planning system that produces a route plan whose execution would require driving beyond the limits is producing a plan that is unlawful to execute, and the dispatching carrier is liable for both the plan and the execution.

IMO Resolution MSC.428(98) requires that ship safety-management systems incorporate cyber-risk management as part of the International Safety Management (ISM) Code, with effect from the first annual verification of a ship's Document of Compliance after 1 January 2021. Together with MSC-FAL.1/Circ.3 guidelines on maritime cyber risk management and BIMCO/INTERTANKO/OCIMF cybersecurity guidelines, these obligations require shipping companies to identify, protect, detect, respond, and recover against cyber threats to navigation, propulsion, cargo handling, and safety systems. SOLAS Chapter V navigation requirements, the IMDG Code for dangerous goods, and the Maritime Labour Convention all overlay further operational obligations whose execution must be planned, evidenced, and auditable.

The IATA Operations Manual codifies the operational procedures for member airlines covering flight operations, cabin operations, ground operations, security, and cargo, complementing the ICAO standards and recommended practices in Annexes 6 and 18. The IATA Dangerous Goods Regulations implement the ICAO Technical Instructions for the Safe Transport of Dangerous Goods by Air, governing acceptance, packaging, marking, documentation, and segregation. Air cargo planning must satisfy weight-and-balance, dangerous-goods compatibility, security-screening (TSA's Certified Cargo Screening Program in the United States, ACC3 and KC3 in the European Union), and crew-duty regulation (FAR Part 117 in the United States, EASA FTL in Europe, ICAO Annex 6 globally) constraints simultaneously, and the constraints interact: a routing change to accommodate weather can break duty-time compliance, push dangerous-goods segregation past acceptable limits, or invalidate the security screening chain.

ISA-95 (IEC 62264) defines the functional hierarchy and information exchange between enterprise (Levels 4 and 3) and manufacturing or operational systems (Levels 2, 1, and 0), the architectural framework within which planning systems coordinate with execution systems for warehousing, port operations, and intermodal handling. ISA-99/IEC 62443 provides the cybersecurity reference architecture for the operational technology layer, with zone-and-conduit segmentation, security levels, and lifecycle requirements that constrain how planning systems may interact with the operational systems they direct. NIST Cybersecurity Framework 2.0 provides the overarching framework against which the integrity of the planning systems is measured, with explicit Govern function expectations around supply-chain risk and software integrity. The Department of Defense's Joint All-Domain Command and Control (JADC2) initiative, with its Combined Joint All-Domain Command and Control (CJADC2) implementations, sets the integrity, latency, and joint-operability expectations for logistics planning that supports multi-modal, multi-domain operations, where planning artifacts must be defensible across services, coalition partners, and operational domains.

Each of these frameworks specifies what must be true at execution time, but execution is the moment the plan touches the world. Planning that fails to anticipate the constraints, that fails to maintain validated alternatives, or that fails to expose the lineage of why a particular plan was chosen produces operations that may technically comply at the moment of dispatch and yet break compliance the moment a contingency forces a deviation. The regulatory framework is therefore a planning-time obligation as much as an execution-time one.

Architectural Requirement

Read together, the regulatory framework imposes seven architectural requirements on any system that purports to plan logistics operations. First, plans must be representable as objects whose structure is inspectable, not as the opaque output of an optimizer. The constraints that bound the plan, the alternatives that were considered, the contingencies that were prepared, and the lineage of decisions that led to the chosen plan must all be available for evaluation by humans, by audit systems, and by downstream agents that will execute the plan.

Second, alternatives must be first-class, not implicit. Conventional optimizers produce a single best plan and discard the search tree; when conditions change, the optimizer is invoked again and the alternatives are re-derived. The architectural requirement is stronger: validated alternatives must persist as governed objects, ready for activation, with their own lineage of evaluation against the same constraint set as the promoted plan.

Third, exploration must be contained. Speculative alternatives that have not been validated against operational, safety, and security constraints must not influence operational decisions until they have been promoted through validation. The containment boundary is a governance primitive, not an optimization detail; it is the mechanism by which a planner can explore aggressive options without risking that the exploration leaks into execution. In safety-critical environments (air cargo, hazardous-materials transport, maritime navigation, defense logistics), the consequence of a speculative branch escaping containment is not a degraded outcome; it is an unsafe operation.

Fourth, constraints must be expressible as policy that travels with the plan. FMCSA HOS rules, IATA dangerous-goods compatibility, IMO ISM safety-management requirements, and JADC2 integrity expectations must be evaluable at every node of the planning graph, not as a final post-hoc check. A plan that violates a constraint at an intermediate state is a plan that cannot be safely executed even if the final state happens to comply, because the contingency activations along the path will require the intermediate states to be lawful as well.

Fifth, the planning lineage must be tamper-evident. The reasoning that led to the chosen plan must be reconstructable for audit by safety regulators, by security investigators, by liability insurers, and by command authorities in the JADC2 context. A planning system whose lineage can be silently rewritten produces decisions whose defense, when challenged, depends on the diligence of the operator rather than on the integrity of the system. NIST CSF 2.0's integrity expectations, applied to planning systems rather than to data systems, demand the same cryptographic grounding that the agent and lineage primitives provide elsewhere.

Sixth, executive aggregation across planning agents must be coherent. Large logistics operations involve dozens or hundreds of planning agents managing different segments of the network, different modes, different time horizons, and different fleets. Conflicts among their plans, two routes both relying on the same constrained bridge, two flights both demanding the same crew, two warehouse allocations both reserving the same dock door, must be detected before commitment, not discovered at execution. The architecture must aggregate plans into an executive view in which conflicts are first-class and resolution is governed.

Seventh, planning must integrate with the operational technology layer through the ISA-95 functional hierarchy and the ISA-99/IEC 62443 cybersecurity zoning. A plan that requires an operational system to execute a particular sequence must produce instructions that flow through the appropriate zone-and-conduit boundaries, with authentication, integrity, and authorization grounded in the IEC 62443 security levels assigned to the systems involved. Planning that bypasses the architectural boundaries between enterprise and operational technology is planning that creates cybersecurity exposure as a side effect of optimization, which is precisely the failure mode that ISA-99 and IEC 62443 exist to prevent.

An architecture that satisfies these seven requirements treats planning as a governed cognitive process whose artifacts are first-class objects: planning graphs with promoted, contingent, and speculative branches, with lineage, with policy-grounded constraints, and with executive aggregation. The forecasting engine is the realization of that architecture as a primitive that any logistics agent can use.

Why Procedural Compliance Fails

The current state of logistics planning is procedural in two distinct senses. Inside the optimizer, planning is a single-shot computation that produces a best plan against current inputs and discards the rest. Outside the optimizer, compliance is a procedural overlay: the carrier's compliance team reviews dispatch outputs against HOS rules, the airline's load planners cross-check dangerous-goods compatibility against an IATA database, the shipping line's safety-management system audits planned voyages against ISM cyber-risk criteria, and so on. Each procedural overlay assumes that the optimizer's output is the artifact under review, and each overlay produces its own procedural artifact that becomes the documentation of compliance.

This procedural model fails in three structural ways. First, alternatives are lost. When conditions change, when a driver runs short on hours, when a port closes, when a flight diverts, when a bridge is restricted, the original plan is no longer feasible, and the optimizer is invoked again to produce a new plan from scratch. The alternatives that were considered the first time, including alternatives that may now be more appropriate, are not available; they were never persisted as inspectable objects. Re-optimization is computationally expensive, and the operational cascade of a complete plan change ripples through the rest of the network: drivers re-tasked, dock doors re-assigned, customer commitments renegotiated, fuel and crew re-positioned. The cascading cost of re-optimization is a known and documented operational pathology in trucking, intermodal, and air-cargo operations.

Second, contingency is improvised. When a known disruption pattern (weather, port congestion, capacity loss) materializes, the operational response is improvised by dispatchers and load planners, who fall back on heuristic alternatives developed informally over their careers. The heuristic alternatives are not validated against the full constraint set in advance, because they exist in human memory rather than in the planning system. A driver-redispatch decision made under time pressure may break HOS compliance in a way that becomes visible only on the next ELD download; a load-replanning decision made to recover an air-cargo schedule may push dangerous-goods segregation past acceptable limits in a way that is detected only at the receiving station. The procedural compliance overlay catches some of these failures but not at planning time, by which point the operational and reputational cost has already been incurred.

Third, the planning lineage is not auditable. When a regulator, an insurer, or an investigator asks why a particular plan was chosen, the answer is reconstructed from optimizer logs, dispatcher recollections, and email threads. The optimizer's internal search tree, if it was retained at all, is not in a form that supports audit. The planning lineage that ought to anchor liability, safety, and security investigations is not durable, and the operational records that exist (ELD downloads, voyage data recorders, ATC tapes, JADC2 messaging logs) are evidence of execution rather than evidence of planning. The gap between planning and execution evidence is a structural deficiency that procedural compliance has never been able to close, and it has produced material liability and safety-investigation failures, including in NTSB and IMO casualty investigations where the question of why a particular routing or schedule was chosen turned out to be unanswerable from the records that the operator had retained.

Optimizer-only planning is also brittle to constraint additions. Adding a new constraint, a new sanctioned-entity routing restriction, a new dangerous-goods segregation rule, a new cybersecurity zoning requirement, requires changing the optimizer's objective function or constraint expression, which requires development, validation, and deployment cycles measured in months. The pace of regulatory change in logistics, particularly in maritime cyber-risk, sanctions enforcement, and dangerous-goods regulation, has outpaced the cadence at which carrier optimizers can absorb new constraints, with the gap filled by procedural overlays that do not actually shape the plan.

Finally, optimizer-only planning is hostile to executive aggregation. Each planning agent (truck dispatch, intermodal coordination, warehouse allocation, port scheduling, air-cargo load planning, vessel voyage planning) runs its own optimizer with its own model and produces output that other agents consume only as inputs. Conflicts among agents emerge at execution rather than at planning, because the planning artifacts are not in a form that supports aggregation. The JADC2 expectation of joint, multi-domain, machine-coordinated planning is unattainable without a planning artifact that is structured for aggregation; conventional optimizer output is not.

What AQ Primitive Provides

The Adaptive Query forecasting engine represents each logistics plan as a planning graph: a structured cognitive object whose nodes represent decisions, whose edges represent dependencies and alternatives, and whose branches are classified by their evaluation status. The promoted branch represents the current operational plan, signed by the appropriate authority and ready for execution. Contingency branches represent validated alternatives that have passed the same constraint evaluation as the promoted branch and are ready for activation when conditions change. Speculative branches represent options that have not yet been operationally validated; they are inspectable but contained, and they cannot influence operational decisions until promoted.

The constraint set against which branches are evaluated is expressed as policy that travels with the planning graph. FMCSA HOS rules, the ELD-required RODS structure, IMO MSC.428(98) safety-management expectations, the IATA Operations Manual and Dangerous Goods Regulations procedures, ISA-95 functional hierarchy expectations, ISA-99/IEC 62443 zone-and-conduit boundaries, NIST CSF 2.0 control objectives, and the JADC2 integrity expectations are encoded as machine-evaluable invariants over the graph's nodes and paths. A branch that fails any invariant at any node is structurally ineligible for promotion, and the failure is surfaced as a property of the branch rather than as an exception detected by an external compliance overlay.

When conditions change, the agent does not re-optimize from scratch. It evaluates which contained branches are now more appropriate than the promoted branch under the new conditions. If a route is blocked, the contingency route, already structured, already validated against HOS, dangerous-goods, security, and cybersecurity constraints, is promoted. The promotion is a governed transition: the authority that promotes the branch is signed, the lineage records why the promotion occurred, and downstream agents (execution systems, ELD platforms, customs and security filings, JADC2 messaging endpoints) consume the promoted branch as the new operational truth. Operational disruption is minimized because the alternative was already planned, already validated, and already structurally ready.

Containment is enforced cryptographically. Speculative branches are marked as such in the graph's structure, and the agents and execution systems that consume the graph are bound by policy to ignore speculative branches for operational purposes. A logistics agent might speculatively explore a new distribution route that could reduce transit times; the exploration occurs within the containment boundary, and the speculative route is evaluated against vehicle availability, driver hours regulations, fuel costs, customer delivery windows, dangerous-goods compatibility, and cybersecurity zoning. Only after the speculative plan passes all operational validation does it become eligible for promotion, and the promotion is itself a signed event that any later auditor can verify. Until then, the speculative branch consumes only computation, not operational resources.

Executive aggregation is a property of the planning-graph layer. Multiple planning agents managing different segments of the network publish their planning graphs into an executive view that aggregates across agents, identifying conflicts (resource contention, schedule collisions, capacity over-allocation) and optimization opportunities (consolidation, repositioning, joint routing) that individual agents cannot see. When two route-planning agents both rely on the same bridge whose load rating cannot accommodate both, the executive aggregation detects the conflict before either commits, and the resolution is governed by policy expressed at the executive level. In the JADC2 context, the same primitive supports joint planning across services and coalition partners, with each participant's planning graph contributing to a federated executive view whose integrity is grounded in the cryptographic primitives of the agent platform.

The planning lineage is durable, signed, and auditable. Every node of the graph records the reasoning that produced it, the constraints it satisfied, and the alternatives that were considered and contained. When a regulator asks why a plan was chosen, the answer is a walk over the lineage, not a reconstruction from logs. When a safety investigator asks what alternatives were available and why they were not chosen, the answer is the contained branches and their evaluation against the constraint set. When an insurer asks what contingencies were prepared, the answer is the contingency branches that were validated and ready for activation. The forecasting engine produces planning artifacts that are evidentiary in the same sense that the execution artifacts (ELD downloads, voyage data recorders, JADC2 logs) are evidentiary, closing the gap between planning evidence and execution evidence that procedural compliance has never closed.

Compliance Mapping

FMCSA Hours of Service compliance becomes a property of the planning graph rather than a post-hoc check. HOS invariants are evaluated at every node and along every edge, and a branch that would require driving beyond the limits is structurally ineligible for promotion. ELD-required RODS data are emitted as a projection of the graph's execution lineage, aligned with the dispatcher's expected schedule and reconciled to the actual ELD output as the operation proceeds. Adverse-conditions exceptions, sleeper-berth split provisions, and short-haul exemptions are expressed as policy options rather than as ad hoc dispatcher overrides, and their use is surfaced in the lineage for compliance review.

IMO MSC.428(98) cyber-risk-management expectations are satisfied by treating the planning graph itself as a cyber-relevant artifact whose integrity is cryptographically grounded. The ISM Code's safety-management documentation references the planning lineage as evidence of how voyage decisions are governed, and the cyber-risk-management documentation references the cryptographic primitives that protect the planning artifacts. Voyage planning under SOLAS Chapter V and IMDG cargo segregation under the IMDG Code are evaluated as invariants at every node of the voyage planning graph, with contingencies for adverse weather and port closures pre-validated rather than improvised.

The IATA Operations Manual procedures and the Dangerous Goods Regulations are encoded as policy on air-cargo planning graphs. Weight-and-balance, dangerous-goods compatibility, segregation, security-screening chain integrity, and crew-duty regulation are evaluated jointly at every node, eliminating the class of failures in which a routing change to accommodate weather breaks duty-time compliance or invalidates the screening chain. ICAO Annex 6 flight-time-limitation calculations, FAR Part 117 in the United States, and EASA FTL in Europe are jurisdiction-specific policies composed onto the planning graph for the relevant flight, with the graph's lineage providing the evidentiary trail for the operator's safety management system.

ISA-95 functional-hierarchy integration is expressed as an emission contract from the planning graph to the operational technology layer. Promoted branches produce instructions to Level-2 control systems, Level-1 PLCs and SCADA endpoints, and Level-0 sensors and actuators through conduits whose security characteristics are governed by ISA-99/IEC 62443 zone-and-conduit policies. The cybersecurity zoning is expressed as policy on the planning graph itself, so that a plan that would require an unauthorized cross-zone interaction is structurally ineligible for promotion. NIST CSF 2.0 Govern, Identify, Protect, Detect, Respond, and Recover functions apply directly to the forecasting engine's identity, signature, lineage, and emission infrastructure.

JADC2 integrity expectations align naturally with the planning-graph primitive. Joint planning artifacts are signed, lineage-extended, and aggregated across services and coalition partners through the executive graph, with conflicts surfaced before commitment and resolutions governed by policy expressed at the joint level. The CJADC2 implementation's specific requirement that planning artifacts be defensible across operational domains is served by the same lineage that serves civilian regulators, eliminating the parallel evidentiary regimes that today complicate dual-use logistics. Sanctions, export-control (EAR, ITAR), and trusted-systems requirements compose onto the same graphs without requiring parallel planning systems.

Adoption Pathway

Adoption begins with a single planning domain in a single operational segment, typically over-the-road truck dispatch where FMCSA HOS compliance and the ELD Mandate already produce strong incentives for structural rather than procedural compliance. The carrier deploys the forecasting engine alongside the existing optimizer; dispatchers continue to use familiar interfaces, while the planning graph accumulates the alternatives, contingencies, and lineage that the optimizer alone does not produce. Pilot metrics focus on three things: the rate at which contingency branches are activated under disruption, the time-to-decision when conditions change, and the audit defensibility of the planning lineage when sampled against ELD-derived execution records.

The first integrating operational system is the dispatch interface that emits driver assignments and the ELD platform that records execution. The forecasting engine emits the promoted branch as the dispatch instruction, the contingency branches as standby alternatives that the dispatcher can activate without re-running the optimizer, and the lineage as the audit-ready record. RODS reconciliation between the planning graph's promoted branch and the actual ELD output becomes a structural quality metric, surfacing the gap between plan and execution as a first-class signal rather than as an after-the-fact compliance question.

From the trucking beachhead, adoption expands along three axes: more planning domains in the same operation (intermodal coordination, warehouse allocation, port scheduling, last-mile dispatch), more modes in the same network (air cargo with IATA OM and DGR policies, maritime voyage planning with IMO MSC.428(98) and IMDG policies), and more compliance regimes mapped onto the same graphs. ISA-95 integration follows naturally in operations with substantial OT footprint (port operations, intermodal terminals, automated warehouses), with the planning graph emitting instructions through ISA-99/IEC 62443-compliant conduits. NIST CSF 2.0 governance metrics derive from the platform's own monitoring, eliminating the gap between security reporting and operational reality.

Executive aggregation comes online once two or more planning agents are operating in the same forecasting-engine deployment. The executive graph aggregates plans across agents, surfaces conflicts before commitment, and supports cross-agent optimization opportunities (consolidation, repositioning, joint routing) that no individual agent could see. For defense logistics under JADC2, the executive graph becomes the substrate for joint and coalition planning, with cryptographic primitives providing the integrity that JADC2 implementations require. For civilian multi-modal logistics, the executive graph supports the cross-modal coordination that today depends on bilateral integrations between mode-specific planning systems.

Over a multi-year horizon, the procedural compliance overlays continue for regulatory continuity while the structural enforcement closes the gaps that procedural overlays cannot. The optimizer becomes a node in the planning graph rather than the planning system itself; new constraints (regulatory, contractual, operational) are absorbed as policy on the graph rather than as code changes in the optimizer; and the planning lineage becomes the durable evidentiary record that bridges planning and execution. The end state is a logistics operation in which every plan is a structured cognitive artifact, every alternative is a governed object, every contingency is pre-validated, every promotion is auditable, and every conflict is detected before commitment, with FMCSA, IMO, IATA, ISA-95, ISA-99/IEC 62443, NIST CSF, and JADC2 obligations satisfied as properties of the planning artifacts themselves rather than as aspirations of the planners. Operational resilience, the capacity to adapt under disruption without breaking compliance or losing the evidentiary trail, becomes a structural property of the system rather than a heroic property of its operators.