Constraint modelling
Time windows, capacities, priorities, compatibility rules, service times and rules specific to each customer, area or vehicle.
Technology
An enterprise-grade optimisation engine.
The difference between planning and optimisation lies in the engine: how constraints, objectives and operational rules are modelled. LOGISPLAN uses proprietary technology developed by Evolution Algorithms to solve genuinely complex planning scenarios.
Technical foundations
Multi-objective optimisation
Balancing cost and service through penalties, plan stability, time-window compliance and operational KPIs.
Heuristics and iterative improvement
Finding feasible solutions and improving them progressively under constraints, avoiding theoretical plans that cannot be executed.
Evolutionary algorithms
Exploring alternatives with evolutionary and genetic-algorithm techniques to avoid local optima in complex scenarios.
Scenarios and simulation
Comparing operational alternatives—fleet, shifts, areas and changes in demand—with measurable impact.
Integration-ready architecture
An integration approach for order, master-data and execution systems that automates the planning workflow.
Technology explained with practical content
This page can grow with technical material on how constraints are defined, scenarios are assessed, metrics are optimised and plan feasibility is validated. The goal is to avoid generic copy and document the approach precisely.