A heuristic ceiling point algorithm for general integer linear programming
Management Science
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General Purpose Heuristics for Integer Programming—Part II
Journal of Heuristics
Exploring relaxation induced neighborhoods to improve MIP solutions
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
Pivot, Cut, and Dive: a heuristic for 0-1 mixed integer programming
Journal of Heuristics
Concave programming for minimizing the zero-norm over polyhedral sets
Computational Optimization and Applications
Operations Research Letters
A feasibility pump heuristic for general mixed-integer problems
Discrete Optimization
Improving the feasibility pump
Discrete Optimization
Pivot and shift-a mixed integer programming heuristic
Discrete Optimization
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Finding a feasible solution to a MIP problem is a tough task that has received much attention in the last decades. The Feasibility Pump (FP) is a heuristic for finding feasible solutions to MIP problems that has encountered a lot of success as it is very efficient also when dealing with very difficult instances. In this work, we show that the FP heuristic for general MIP problems can be seen as the Frank-Wolfe method applied to a concave nonsmooth problem. Starting from this equivalence, we propose concave non-differentiable penalty functions for measuring solution integrality that can be integrated in the FP approach.