1. Integer Programming Heuristics and Applications in Industrial Engineering and Business Analytics
Research director: Marko Mäkelä ▪ Supervisor: Yury Nikulin
Key research questions:
What are efficient models (exact, heuristic) for routing and scheduling in a dynamic network?
How does the model perform in an uncertain graph when applied in real situation?
How can the reliability of a predicted route be measured? How can it be improved?
Can the model be incorporated as a part of autonomous navigation?
The research is sponsored by Business Finland (former Tekes)
Project leader: Jukka Heikkonen

2. Plans towards completion and beyond:
Publications:
Maskooki A, Nikulin Y, Bi-objective routing and scheduling in a dynamic network: An application to maritime logistics (ready for submission)
Maskooki A, Nikulin Y, Modeling efficient routing in a dynamic network: a synergy of time dependent TSP and single machine scheduling problem, 30th European Conference on Operational Research (EURO 2019) (accepted)
Nayyeri M, Sadoughi Yazdi H, Maskooki A., Rouhani M, Universal approximation by using the correntropy objective function, IEEE Transactions on Neural Networks & Learning Systems, 29(9), 4515−4521, 2018.
Nayyeri M, Maskooki A, Monsefi R, ”A new spars learning machine”, Neural Processing Letters,46(1), 15−28, 2017.
Maskooki, A, ”Improving the efficiency of a mixed integer linear programming based approach for multi-class classification problem”, Computers & Industrial Engineering, 66(2), 383−388, 2013.
Maskooki, A, Adibmanesh, A, ”Modeling optimal nutrition for military through linear programming and a case study on the target population”, Proceedings of Sixth Congress Association Geopolitics of Iran, 2013 (in Persian).
Plans towards completion and beyond:
An evolutionary algorithm for moving-target traveling salesman problem with time windows (ongoing)
Assessing the prediction uncertainty of a route optimization model in real situation by rescheduling (ongoing)
Updating route optimization model by using a local prediction method (planned)
Routing and scheduling in an uncertain dynamic networks (planned)