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New concave penalty functions for improving the Feasibility Pump

Marianna De Santis (mdesantis***at***dis.uniroma1.it)
Stefano Lucidi (lucidi***at***dis.uniroma1.it)
Francesco Rinaldi (rinaldi***at***dis.uniroma1.it)

Abstract: Mixed-Integer optimization represents a powerful tool for modeling many optimization problems arising from real-world applications. The Feasibility pump is a heuristic for finding feasible solutions to mixed integer linear problems. In this work, we propose a new feasibility pump approach using concave non-differentiable penalty functions for measuring solution integrality. We present computational results on binary MILP problems from the MIPLIB library showing the effectiveness of our approach.

Keywords: Mixed integer programming, Concave penalty functions, Frank-Wolfe algorithm, Feasibility Pump

Category 1: Integer Programming ((Mixed) Integer Linear Programming )

Category 2: Nonlinear Optimization

Citation: This manuscript is a previous version of the following paper: M. De Santis, S. Lucidi and F. Rinaldi. "A new class of functions for measuring solution integrality in the Feasibility Pump approach." SIAM Journal on Optimization, 23(3), pp. 1575-1606, (2013)

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Entry Submitted: 07/01/2010
Entry Accepted: 07/01/2010
Entry Last Modified: 10/04/2016

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