Real-Time Scheduling for Field Service Operations and Last Mile Delivery

Most operational teams are still working with static daily plans built hours or even days earlier, making reactive firefighting the norm rather than seamless responsiveness. And this will incur extra costs:

• Late deliveries erode customer trust
• Fleet underutilization drives up cost-per-mile
• High wait times impact patient or customer safety
• Inefficient travel increases CO₂ emissions

Real-time scheduling enables routes and assignments to adapt continuously throughout the day. Rather than rebuilding schedules from scratch when changes occur, the Solvice API uses initial-state optimization to update plans without disrupting work that has already started. This API-first approach integrates directly into existing systems, allowing you to add dynamic routing capabilities without rebuilding your operational stack.

The business impact is measurable. According to McKinsey, logistics operations that embrace dynamic planning can improve fleet productivity by 20–30% and significantly reduce costs. Organizations implementing real-time scheduling report reduced cost-per-delivery, higher fleet utilization, and improved SLA compliance.

How Real-Time Scheduling Works

Real-time scheduling means routes and resource assignments continuously adapt to current conditions. With Solvice:

• New orders or service requests can be automatically inserted into active schedules.
• Schedules are reoptimized based on current vehicle locations, availability, time windows, capacities, and traffic conditions.
• Your system can respond instantly to changes without manual replanning.
• Operations prevent delays rather than reacting to them after they occur.

The Solvice Route Optimization API provides an optimization engine built for continuous adaptation. After creating an initial schedule, your application can trigger recalculation at any moment—when new jobs arrive, appointments are canceled, or vehicles become unavailable.

Technical Implementation: Two-Phase Optimization

The Solvice API is built for continuous optimization through a two-phase approach:

Phase 1: Bulk Planning

Start each period (day, week, …) with comprehensive route optimization using the asynchronous solve endpoint. This creates the foundation schedule that accounts for all known jobs, vehicle capabilities, time windows, and constraints.

Phase 2: Real-Time Adjustments

Throughout the day, use the synchronous solve endpoint to update the schedule based on the current operational state rapidly.

The API supports initial-state preservation—you can provide the current status of in-progress routes using the initialResource and initialArrival fields. This allows the algorithm to focus only on what needs to change rather than rebuilding the entire schedule, avoiding unnecessary disruption to work that's already started.

You maintain full control over schedule stability through planned constraints:

• Lock existing assignments using plannedResource constraints to keep committed appointments fixed
• Preserve specific time slots while allowing flexibility elsewhere
• Insert new jobs incrementally and receive instant placement suggestions
• Control which portions of the schedule can be modified to balance responsiveness with customer commitment stability

The API evaluates vehicle status, remaining capacity, time windows, priorities, and skill requirements, returning an updated schedule in under 5 seconds. This combination of speed, state preservation, and fine-grained control makes it straightforward to build real-time dispatch capabilities directly into your platform.

Industry Use Cases: Adapt Faster, Serve Better

Last^-Mile Delivery

Scenario: A customer requests a new pick-up order mid-route.

Result: Real-time scheduling dispatches the closest driver with sufficient capacity, reducing pick-up time by up to 25%.

NEMT & Home Healthcare

Scenario: An urgent non-emergency medical transport request is added for a high-priority patient.

Result: The API reallocates drivers or caregivers based on current availability and travel time, reducing wait times and improving care outcomes.

Field Service & Home Repairs

Scenario: A technician finishes a job early, or another task is delayed.

Result: The API reassigns the next job dynamically to maximize technician utilization and reduce idle time.

Construction & Waste Collection

Scenario: Unexpected traffic delays block access to a site.

Result: Schedules are adjusted automatically, and fleets are redirected to maintain service windows without manual dispatcher intervention.

Ride Hailing & Paratransit Services

Scenario: New ride requests arrive continuously.

Result: The optimization engine matches requests to drivers using the most efficient dispatch strategy, balancing wait times and driver utilization.

Business Impact: Measurable Improvements

Organizations implementing real-time scheduling with optimization algorithms report consistent operational gains:

• Higher fleet utilization — Better job allocation reduces idle kilometers and driver downtime
• Reduced cost-per-delivery — Shorter routes and optimized sequencing decrease fuel consumption
• Faster response to demand spikes — Dynamic assignment capabilities maintain service levels during peak periods
• Improved on-time performance — Proactive schedule adjustments prevent late arrivals before they occur
• Fewer manual interventions — Automated re-optimization reduces dispatcher workload and allows focus on exception handling
• Lower carbon footprint — More efficient routing reduces fuel consumption and emissions per job
• Enhanced customer experience — Real-time ETAs and faster response times improve satisfaction and retention.

According to Gartner, over 50% of logistics organizations plan to invest in real-time visibility and dynamic optimization capabilities by 2025. Statista reports that the global on-demand delivery market is projected to exceed $600B by 2027, driven by consumer expectations for instant responsiveness.

The Path to Autonomous Operations

Real-time scheduling forms the operational foundation for the next generation of logistics and service delivery. As organizations transition from manual decision-making toward intelligent automation, dynamic re-optimization becomes the core enabler of advanced capabilities:

Autonomous Dispatching

When schedules can be recalculated instantly based on the latest state of jobs, vehicles, and constraints, dispatch decisions can be fully automated. Real-time optimization becomes the engine behind autonomous resource assignment and reassignment, eliminating the need for human intervention in routine dispatch decisions.

Self-Healing Supply Chains

Disruptions such as delays, cancellations, or equipment failures trigger immediate recalculation, creating updated plans without human intervention. Real-time scheduling enables supply chains to adapt in motion—identifying issues and correcting course before they impact service-level agreements.

Carbon-Efficient Routing

With sustainability mandates tightening globally, organizations need to minimize fuel usage and emissions at every operational moment. Dynamic route recalculation enables continuous selection of greener paths and maximizes vehicle utilization, reducing CO₂ emissions per job or kilometer.

Advanced Customer Engagement

When schedules update in real time, customers receive live ETAs, instant confirmations, and rapid rescheduling options. This enables more interactive, transparent, and premium service experiences that build trust and differentiate service quality.

As static planning becomes obsolete and always-adapting operations become standard, operational agility will determine competitive position. Real-time scheduling provides the infrastructure for automation, intelligence, and sustainability at scale.

Implementation Resources

The Solvice API provides comprehensive documentation for implementing real-time scheduling:

Technical Guide: Detailed implementation patterns for job insertion, cancellation handling, and resource unavailability
docs.solvice.io/guides/vrp/features/real-time-scheduling

API Explorer: Interactive environment for testing real-time scheduling scenarios with visual route updates
www.solvice.io/api-explorer

Integration Support: Questions about implementing real-time scheduling for your use case? Our team can provide architectural guidance and integration support.

‍

Real-time scheduling transforms field operations from reactive firefighting to proactive, continuous optimization.

‍