Organizing travel and business trips both efficiently and sustainably can be complex at times. Logistics specialists at the JKU have developed an effective algorithm.
Climate change is a hot topic, meaning traffic is also a point of discussion. Planning travel and business trips effectively and sustainably can sometimes prove to be rather complex. As part of two projects, logistics experts at the Johannes Kepler University Linz have created a process.
Last year, the transportation sector in Austria clearly missed the target of 21.8 million tons of CO2 as outlined in Austria's Climate Protection Act. In all, traffic in Austria has emitted almost seven million tons more CO2 over the past four years than stated in the Climate Protection Act. Better and more efficient travel planning would not only be better for the environment, it would also save time, money and nerves. In this regard, shared community initiatives and companies in particular are interested in these kinds of planning options. JKU logistics expert Miriam Enzi explains problem: “It sounds simple enough, but it is incredibly complex as there are various aspects and different priorities. Do I want to drive or take the train? Would I rather get there as quickly as possible or would I rather minimize travel costs?"
Taking Personal Preferences into Account
While working at the Institute for Production and Logistics Management under the management of Prof. Sophie Parragh, Miriam Enzi developed an algorithm for closed groups to address this exact issue. "A closed group means that, for example, a company can use this to process and optimize employee travel planning." The special part: “Although we can find a reasonably good solution fairly quickly, it is only an approximation. Our program can provide an exact solution - and very quickly. The algorithm not only provides the best possible solutions, but suitable solutions for everyday use."
Enzi further explained: "In more precise terms, the program provides a certain range of solutions that give us viable options in terms of time and money. The company can then say: As Employee A would prefer to get to the destination quickly, he can take a company car at 5:00 pm. Employee B can take the train at 9.15 am, and so on." It is a win-win situation as group members get the best travel option that takes their preferences in terms of means of transportation and time constraints into account. The company can best use its fleet of vehicles and handle travel management in a more cost-effective way, reducing empty kilometers and generating less CO2.
Providing the Perfect Solution
Enzi can offer the program in four stages. While Stage 1 can plan travel for 300 people in just a few seconds, the sequence of trips still has to be specified. The highest level takes a bit longer, but manages only 20 travelers. Enzi added, “In this case, however, the program also defines the best sequence of trips.”
Miriam Enzi initially worked on optimization issues at AIT as well as at CentraleSupélec in France as part of the climate fund project SEAMLESS, which focused on developing car-sharing solutions for companies. Her work as part of the FWF project "MOMIP: Multi-Objective (Mixed) Integer Programming" at the JKU goes beyond that. The designed algorithm not only analyzes different solutions by weighing costs and user-friendly aspects differently, but it can also be easily used by other interest groups. What is the logistics expert particularly proud of? Ms. Enzi added, "The algorithm not only works, it has also become very refined and sophisticated."
