Application of Mixed Integer Optimization for Solving Complex Inventory Problems and Problems Stemming from Metabolic Engineering
Abstract: In this talk, I focus on the application of exact and heuristic methods to solve general mixed integer problems, and in particular: inventory problems combined with other decisions such as distribution, supplier selection, vehicle routing, etc (called complex inventory problems), and interesting problems arising from metabolic engineering. In order to solve complex inventory problems, I first consider substructures (relaxations) of such problems which are obtained by the coherent loss of information. The polyhedral structure of those simpler mixed integer sets is studied to derive strong valid inequalities. Finally those strong inequalities are included in the branch-and-cut and cutting-planes frameworks to solve the general mixed integer problems. Regarding the problems stemming from metabolic engineering, I exploit the concept of multi-objective optimization to deal with mixed integer problems.
Bio: Mahdi Doostmohammadi received the B.Sc. and M.Sc. degrees in applied mathematics from the University of Isfahan, Iran, in 2004 and 2007, respectively, and the Ph.D. degree in operations research from the Universidade de Aveiro, Portugal, in 2014. He is currently a Post-Doctoral Researcher with the Instituto Superior Técnico, University of Lisbon, Portugal, and also a member of the Centro de Investigação e Desenvolvimento em Matemática e Aplicações, Universidade de Aveiro. His research interests include mixed integer optimization, mathematical programming, polyhedral theory, and multi-objective mixed integer optimization.