Venue: Industriens Hus — May 3rd, 2016
Registration is closed
Anders Dohn & Tor JustesenManaging Partner / Principal – Copenhagen OptimizationChanging the world of airport planning
Most people have travelled through airports many times and have seen the operation of an airport from the passenger’ perspective. It is the ambition of the airport to make the passenger experience enjoyable, un-stressful and as smooth as possible. At the same time, there are a number of other operational parameters, which have a high priority in the airport operation, such as minimizing costs, ensuring satisfied employees, and creating a robust operation.When looking “under the hood”, the planning and execution of an airport operation is complex and to get the most value for money, careful planning is required. We describe how operations research and data analysis take part in creating better and more cost efficient airports. Also, we show some examples of why an operations analyst in an airport is like “a kid in a candy store”.While airport operation is a very interesting area of application, we will also give our view on application of operations research in general. How do you successfully change the way of operating in a large organization and how do you change the mindset of the people involved?
Geir HasleChief Scientist – SINTEFStuck between a rock and a hard place
– The pleasures of practicing OR in a contract research organization
In this talk I will touch upon on the pleasures and hardships of being stuck between academia and industry. I will give a few examples of how OR is used at SINTEF, and address the balance between academic research and consultancy. The main topic will be research and technology development in the area of rich vehicle routing problems.
Karsten Nygaard HenriksenDecision Scientist, Co-founder – QAMPOPlanning psychiatric patient flows: Gains and challenges
The psychiatric sector is met with to very difficult demands:First of all the patients must of course receive the care and treatment sufficient for their condition.Secondly the psychiatric sector must honor citizen rights regarding how long a patient flow can last.The Psychiatric sector consists of lots of different types of specialists, lots of different types of patients and lots of rules regarding what activities a patient must undergo, to receive the right psychiatric treatment.
To plan just one patient flow that corresponds to all demands, and at the same time makes sure the necessary ressources are available can be quite a complicated and time-consuming task. To plan all the patient flows that are sufficient to meet the demand is practically impossible without an algorithmic approach.We developed ‘Flowplanner’ to address this issue, using mathematical programming.We will get into some of the gains we have experienced so far in implementing ‘Flowplanner’. But also address some of the challenges we have met, in the process of trying to systemize, plan and break old habits in a sector with a high degree of professional pride.
Claudia BillingGroup Procurement Analyst – ISSFleet Asset Utilization: An unsuccessful encounter between operations research and operations
An initiative to reduce fleet size was carried out, as part of a deep dive exercise on the Norwegian fleet during summer 2015. The project involved using existing data on vehicle movement, routings, customer locations and service windows to via data simulations and modelling identify areas of improvements that ultimately should lead to a smaller fleet. An external consulting company carried out the “Fleet Asset Utilization” analysis with data simulation, modelling and identification of improvement areas. The project was a pilot case for how to improve fleet size in the full European ISS fleet if successful.This talk addresses the elements that failed in the project, why implementation challenges can and did occur in the merge of operations research and an operational environment, and invites to a discussion about how to translate findings of such a study into generic recommendations leading to a databased application of optimization in an operational organization.
Bart van RiessenBusiness Development and Innovation – Europe Container TerminalsThe Cargo Fare Class Mix problem for synchromodal container transportation
Optimisation of a hinterland transportation network is restricted by planning requirements of customers. Our research shows that by offering a differentiated portfolio of transportation services with varied service levels and fares, customer segments can be targeted to allow more planning flexibility. We show that an optimal Cargo Fare Class Mix (CFCM) can significantly increase revenue for the transportation provider, compared to existing methods. The CFCM differs from the traditional fare class mix in aviation, as the routing of accepted cargo bookings can be changed, in contrast with passenger itineraries. Our interest goes beyond providing a solution model for specific demand scenarios, and we aim to explore the general structure of an optimal fare class mix with booking limits for each fare class considering stochastic demand distributions per fare class. The CFCM problem has multiple applications, e.g. in liner shipping, parcel delivery and web shop inventory management, but we show the application in the context of intermodal container transportation.
Francisco PereiraFull Professor – Technical University of Denmark (DTU)Non-recurrent events in traffic prediction
It is not uncommon that traffic prediction tools and research report very high accuracy. However, the very few such tools that exist in the market seem not to be performing as well as people would like, even though their accuracy may be in fact correspond to the announced. There is a paradox in the field: traffic prediction is not difficult most of the time (the routine conditions), but sometimes it becomes extremely hard (the non-recurrent events), which is often when it is needed! This presentation will focus on ongoing and past work from DTU, MIT, CISUC and Singapore-MIT Alliance for Research and Technology (SMART) related to treatment of non-recurrent events in a traffic prediction system.