Integer Programming and Combinatorial Optimization

Integer programming and combinatorial optimization concern developing theory, methodologies and algorithms that are used to model and solve decision-making problems of discrete choices. For instance, industrial problems requiring communications network design, machine/crew scheduling, plant location, vehicle routing form important classes of optimization problems involving integer variables. Other applications include gene sequencing, sports scheduling, and time-tabling. Current projects in this area at the MORE Institute include designing solution methodologies for applications in inventory management, telecommunications network design and logistics, as well as developing theory and methodologies for mixed-integer programming under uncertainty.

Integer Programming and Combinatorial Optimization

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