We focus on applied operations research. We develop methods for solving difficult decision problems in practice, taking into account real-world conditions and considerations. We implement these methods in high-quality practically usable software and prototypes. We contribute to the state of the art of the research field.
Through decades of working with optimization and operations research we have obtained a deep understanding of the complexities of applied operations research. Companies and organizations increasingly see the need for data-driven decision support and decision automation, and by working closely with our partners we bring our expertise to bear on unsolved problems, solving research questions and enabling innovation. As experts on methods, we believe in the value of cross-pollination, using insights gained in one application domain to support our work in another.
We have broad experience in the full range of methods in the field, including exact mathematical optimization, decomposition methods, metaheuristics and matheuristics. We implement our software in our own libraries that we have refined and extended over many years but also utilize commercial solvers. Our results are used either existing solution vendors, by our partners, or directly by our end users.
We combine a thorough understanding of operations research with a passion for finding solutions that work in practice, all the way to building production-ready software. Through this dual focus we are able to solve hard, practical problems as well as contribute to scientific progress.
We are always open for new opportunities to work on interesting problems. Please get in touch for a discussion of what we can offer, or to hear more about the research work we are doing. Below you can find a selection of our work that you can look at further.
More efficient rail mobility via innovative AI-based methods, by enabling optimized planning of rail replacement services and cost-effective infrastructure investment decisions.
Optimizing Yard Operations (OYO) will provide innovative technology that incorporates optimization algorithms for planning resource-efficient stabling and shunting in train yards.
Efficient warehouse operations are essential in the real world, and current approaches often lack sufficient integration and support for data-driven decisions.
GOTO - Greater Oslo Train Optimization. The GOTO main goal was to transfer the most recent advances in optimization and machine learning to railway traffic management. We developed the methodological groundwork for an Optimization-based Traffic...
Currently, maintenance planning in the railroad domain is predominantly performed manually and involves: Crew scheduling (assigning maintenance tasks to crews dependent on skill set) and job shop scheduling (assign time slots for vehicles to depot...
SINTEF was the research partner in the innovation project OptiSite, led by Spacemaker (now part of Autodesk). The project contributed to developing Spacemaker from a start-up idea to an established product with international presence.
OPSTRA - Optimal Scheduling for next-generation intelligent TRAnsport systems is a pure research project devoted to develop new mathematical optimization models and algorithms for job-shop scheduling problems arising in transportation. The...
Optimal Route Planning (ORP) aims to develop optimization-based algorithms and tools to support a smoother, future-oriented train timetabling process. The ORP Prototype is the first phase of this ambitious project, where a prototype is developed and...
StraTi is a short exploratory research project for extending SINTEF's existing train management tools in order to support Strategic Timetabling.
The CO2REOPT project aims at developing methods and tools for full external transport integration where suppliers, manufacturers and customers share a fully integrated and optimized intermodal supply chain.
The goal of the SmartPower project is to demonstrate the usefulness of modern optimisation methods for demand response applications in energy markets. To this end, we develop a prototype for optimised power matching/load balancing in large scale...
Enabling better collaboration between humans and decision support systems in time-critical complex domains
In the DynamITe competence project, we developed new models, solution methods, and basic software for optimized transport of goods and people in an ever more dynamic world.
This is a large industrial project between Nobina AB in Sweden and SINTEF Optimisation. The project focuses on building a personnel scheduling engine - SkiftOpt - that matches bus drivers to shifts. The engine creates a work schedule for personnel by...
The BONVOYAGE project aims at designing, developing and testing a platform optimizing multimodal door-to-door transport of passengers and goods.
Sports scheduling addresses the problem of assigning a date and venue to each game of a tournament, while taking the wishes and requirements of all stakeholders into account. Scheduling a sports league or a tournament is a combinatorial optimization...
The overall goal of AKTIV is to increase quality of treatment, patient satisfaction, and efficiency in hospitals. This will be achieved by the development of powerful—optimisation based—planning tools that enables more unified planning processes...
Kongsberg Digital is leading the way towards the digitalized energy system of the future with its KogniGrid project.
ENERGYTICS will demonstrate how machine learning and artificial intelligence can increase the value of the new smart meters that are currently being installed in all Norwegian homes.
A solver for generalized Resource Constrained Project Scheduling Problems. With a rich problem model, and an adaptable set of algorithms, it is applicable to a wide range of real world planning- and scheduling problems.
A software component for automatic optimization of rosters
Train dispatcher provides decision support for train controllers. In situations where a train is delayed, other trains may also be delayed as a consequence. The software calculates the a plan that minimizes the total delay across all trains.
SIMADES - a simulator for decision support, validation, testing, training and education.
Optimising Air Traffic Control.
Our Invent software automatically produces optimised plans for maritime transportation of bulk commodities, while keeping storage levels for production and consumption within limits. Typical application areas are transportation of Liquefied Natural...
Spider is a versatile and powerful software component for optimized transportation planning and vehicle routing. It offers a huge potential for savings in transportation through cutting edge optimization algorithms. Spider has been developed by...
A software for computing the optimal (switch) configuration of power distribution grids. The choice of configuration is critical in many DSO decision processes, from long term investment planning to daily operations.
Bringing together international top-level expertise in artificial intelligence and operational experts, SINTEF has developed the Integrated Runway Sequence Manager (IRSM). This solution plans arrival and departure flows as synchronised, integrated...
