Diploma in Routing and Scheduling with Real-World Constraints
Online postgraduate diploma of 800 hours in routing and scheduling with real-world constraints. 8 modules covering VRP variants, distance matrices, operational and legal constraints, exact methods, routing metaheuristics, dynamic dispatching and deployment under Regulation (EC) 561/2006, Regulation (EU) 165/2014 and ISO 14083:2023, with an assigned technical tutor.
Diploma in Routing and Scheduling with Real-World Constraints — studying from the United States
Data science, artificial intelligence and simulation are central to American industry, with major concentrations in the San Francisco Bay Area, Seattle, New York and Boston. Engineering organizations increasingly rely on machine learning, digital twins and high-performance computing to accelerate design, testing and operations. Employers range from large technology companies to aerospace, automotive and energy firms that apply analytics to complex systems. Demand is strong for engineers who combine domain knowledge with modeling, statistics and software skills.
Fees for the United States: US$1,670 (US Dollars), with instalments and employer sponsorship available.
Relevant bodies in the United States
Typical roles
Questions from the United States
Which US bodies relate to data science, AI and simulation engineering?
There is no single licensing body for data science or AI in the US. Relevant professional organizations include the IEEE Computer Society, the Association for Computing Machinery (ACM), and the Society for Industrial and Applied Mathematics (SIAM). Federal guidance such as the NIST AI Risk Management Framework shapes practice. SEIUM's qualifications are private and not accredited by a national body, so recognition is decided by employers.
How do US employers in data and AI regard private online postgraduate qualifications?
US tech firms, financial institutions and research labs generally hire on the basis of portfolios, technical interviews, relevant experience and sometimes advanced degrees. A private online qualification can show structured study, but it is not a standard hiring requirement and each employer weighs it differently. Public projects, code repositories and measurable results tend to matter most.
Is it realistic to study data and AI from the US around a full-time job?
Yes, the programmes are fully online and taught in English, so you can study from home without a student visa. The workload is large: about 1,900 hours for a master's, 800 hours for a postgraduate diploma, and 300 hours for a specialist course. An assigned technical tutor supports you. Fees may be paid in instalments, and employer sponsorship is sometimes available, which you should confirm with your employer.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Classify routing and scheduling problems with real-world constraints.
Build reliable distance and time matrices.
Model operational, legal and resource constraints.
Apply exact methods and understand their practical limits.
Solve large-scale problems with metaheuristics.
Manage dynamic routing under uncertainty.
Deploy route optimisers and measure their real impact.
Who it's for
- Logistics optimisation engineers.
- Route planners who want to move from manual planning to optimisation tools.
- Operations research analysts.
- Field operations managers.
- TMS developers.
- Logistics consultants.
- Engineering or science graduates seeking to enter distribution and parcel delivery.
What you'll work with
- Regulation (EC) 561/2006 (Driving times and rest periods)
- Regulation (EU) 165/2014 (Tachographs)
- ISO 14083:2023 (Quantification of greenhouse gas emissions from transport chains)
- Royal Decree 1561/1995 (Special working hours, Spain)
- EN 16258:2012 (Calculation of energy consumption and emissions in transport)
- OGC GeoJSON (IETF RFC 7946)
- Google OR-Tools
- PyVRP
- VROOM
- OSRM
- Hexaly (LocalSolver)
8 modules
1.1Travelling salesman problem (TSP)1.2Vehicle routing problem (VRP)1.3Variants: CVRP, VRPTW and PDPTW1.4Technician routing and field services1.5Staff assignment and shifts1.6Hard and soft constraints1.7Multiple and hierarchical objectives1.8Solomon and Gehring-Homberger instances1.9The gap between theory and real operations1.10Workshop: analysing the real constraints of a fleet
2.1Address geocoding2.2Distance and time matrices2.3OSRM and Valhalla routing engines2.4Traffic and time-of-day-dependent travel times2.5Access restrictions and heavy vehicles2.6Service times and their estimation2.7Customer data quality2.8Large-scale matrix caching2.9Geographic visualisation of routes2.10Practical exercise: time matrix with OSRM
3.1Multiple time windows3.2Multidimensional capacity: weight and volume3.3Vehicle-customer compatibilities3.4Technician skills3.5Working hours, breaks and driving regulations3.6Return to depot and multiple depots3.7Paired pickups and deliveries3.8Priorities and penalties for unserved customers3.9Fairness constraints between routes3.10Case study: routes under driving-time regulations
4.1Flow formulations for the VRP4.2Branch, cut and price4.3Column generation for routes4.4Constraint programming for scheduling4.5Shift models with MILP4.6Practical limits of exact methods4.7Lower bounds and solution quality4.8Modelling with OR-Tools Routing4.9Modelling with PyVRP and VROOM4.10Lab: VRPTW with OR-Tools
5.1Clarke-Wright savings heuristic5.2Insertion and sweep5.32-opt, or-opt and relocate operators5.4Guided local search5.5Adaptive Large Neighbourhood Search5.6Hybrid genetic search (HGS)5.7Time-limited search5.8Parallelising the search5.9Evaluation with benchmarks5.10Practical exercise: ALNS for a VRP with time windows
6.1Real-time order arrival6.2Reoptimisation and stability6.3Uncertainty in travel times6.4Stochastic and robust routing6.5Waiting and repositioning policies6.6Real-time technician dispatching6.7Simulation to evaluate policies6.8Communication with drivers6.9Real-time indicators6.10Lab: dynamic dispatching simulator
7.1Integration with TMS and FSM7.2Interfaces for planners7.3Manual adjustments and locks7.4Acceptance by drivers and technicians7.5Indicators: kilometres, punctuality and cost7.6Measuring real savings7.7Scaling to several regions7.8Sustainability and emissions7.9Common deployment mistakes7.10Case study: deploying a route optimiser
8.1Real case and constraints8.2Data and matrices8.3Problem model8.4Solution method8.5Computational experiments with real instances8.6Route sensitivity analysis8.7Route deployment proposal8.8Economic assessment of route savings8.9Report and presentation8.10Final project: final review with the tutor
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so the programme is compatible with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Google OR-Tools, PyVRP, VROOM, OSRM and Hexaly (LocalSolver), in free, academic or evaluation versions. Practical work is based on real procedures for solving Solomon benchmark instances, simulating dynamic dispatching with real-time orders and comparing optimised routes against historical routes. Assessment is continuous by module plus the final project.
Standards covered: Regulation (EC) 561/2006, Regulation (EU) 165/2014, ISO 14083:2023, Royal Decree 1561/1995, EN 16258:2012, OGC GeoJSON.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Google OR-Tools, PyVRP, VROOM, OSRM and Hexaly (LocalSolver), using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
Prior technical training or professional experience in the sector (no university degree required), a computer able to run the programme software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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