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Turning Operational Complexity into Executable Plans
Route optimization is often perceived as a simple routing task. In reality, it is one of the most complex decision challenges in logistics and field operations.
Modern operations must simultaneously account for customer expectations, fleet constraints, cost pressures, and service-level commitments. Optimizing routes without modeling this full complexity leads to plans that appear efficient but break down during execution.
At Optiyol, we approach route optimization as a decision intelligence problem, not a standalone routing exercise.
One Engine for Interconnected Routing Decisions
In real operations, routing decisions are deeply interconnected.
Fleet selection influences transportation cost, capacity utilization, and the ability to meet service commitments.
Order allocation impacts service levels, vehicle utilization, route feasibility, and driver workloads.
Stop sequencing affects total distance, travel time, and whether customer time windows can be respected.
None of these decisions operates in isolation. A change in one immediately alters the cost, feasibility, and service performance of the others.
Optiyol brings customers, orders, vehicles, business rules, and maps together in a single optimization engine. Instead of solving these decisions sequentially, the system evaluates them jointly and generates plans that remain optimal under real-world complexity.
Respecting Real-World Constraints by Design
Operational plans fail when constraints are ignored, simplified, or handled manually after planning.
Optiyol’s optimization engine embeds operational constraints directly into the decision model, including:
- Customer receiving hours and multiple time windows
- Driver working hours and maximum route durations
- Vehicle capacity limits and fleet availability
- Zone restrictions and vehicle compatibility rules
- Priority customers, dedicated tours, and order mix constraints
By modeling these constraints from the start, generated routes are feasible by design, not adjusted through last-minute manual fixes.
Flexible Inputs That Reflect How You Operate
Every operation has its own rules, priorities, and exceptions.
Optiyol is designed to adapt to existing operational logic rather than forcing standardized processes. The platform supports a wide range of planning inputs, including:
- Customer locations, service times, and priority levels
- Orders with pickup, delivery, and sequencing requirements
- Vehicles with different capacities, cost structures, and working rules
- Planning parameters that define flexibility and trade-offs
- Real map-based travel distances and travel times
This flexibility ensures that optimization outputs reflect how your operation actually runs on the ground.
Balancing Cost and Service in a Single Plan
Route optimization is inherently multi-objective.
Minimizing cost alone can harm service performance.
Maximizing service levels alone can inflate operational expenses.
Optiyol balances both dimensions simultaneously in a single optimization run.
Cost-related objectives include:
- Transportation cost based on distance and time
- Fleet utilization and fixed vehicle costs
Service-related objectives include:
- On-time delivery performance
- Compliance with capacity, labor, and operational rules
The result is a plan that delivers efficiency without sacrificing reliability.
From Better Routes to Better Decisions
Better routes are a visible outcome.
Better decisions are the real value.
By formalizing constraints, priorities, and objectives into a unified decision framework, Optiyol helps operations teams reduce cost, improve service levels, and plan with confidence under real-world uncertainty.
This is what decision intelligence looks like in logistics and operations.
