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Anahita Hassanzadeh (anahita.hassanzadehgmail.com) Abstract: This paper addresses the value function of a general mixed integer linear optimization problem (MILP). The value function describes the change in optimal objective value as the righthand side is varied and understanding its structure is central to solving a variety of important classes of optimization problems. We propose a discrete representation of the MILP value function and describe a cutting plane algorithm for its construction. We show that this algorithm is finite when the set of righthand sides over which the value function of the associated pure integer optimization problem is finite is bounded. We explore the structural properties of the MILP value function and provide a simplification of the Jeroslow Formula obtained by applying our results. Keywords: Mixed Integer Programming, Stochastic Integer Programming, Parametric Integer Programming, Value Function Category 1: Integer Programming ((Mixed) Integer Linear Programming ) Category 2: Stochastic Programming Citation: Laboratory for Computational Optimization at Lehigh (COR@L), Department of Industrial and Systems Engineering, Lehigh University, Technical Report 14T004. Download: [PDF] Entry Submitted: 08/03/2014 Modify/Update this entry  
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