Mixed-Integer optimization represents a powerful tool for modelling many optimization problems arising from real-world applications. The Feasibility pump is a heuristic for finding feasible solutions to mixedinteger linear problems. In this work, we propose a new feasibility pump approach for...

In this work, we study continuous reformulations of zero-one programming problems. We prove that, under suitable conditions, the optimal solutions of a zero-one programming problem can be obtained by solving a specific continuous problem.

Mixed-Integer optimization represents a powerful tool for modeling manyoptimization problems arising from real-world applications. The Feasibilitypump is a heuristic for finding feasible solutions to mixed integer linear problems. In this work, we propose a new feasibility pump approach using...

We propose a branch-and-bound algorithm for minimizing a not necessarily convex quadratic function over integer variables. The algorithm is based on lower bounds computed as continuous minima of the objective function over appropriate ellipsoids. In the nonconvex case, we use ellipsoids...

Mixed-Integer optimization is a powerful tool for modeling many optimization problems arising from real-world applications. Finding a rst feasible solution represents the rst step for several MIP solvers. The Feasibility pump is a heuristic for nding feasible solutions to mixed integer linear...

Mixed-Integer optimization is a powerful tool for modeling many optimization problems arising from real-world applications. Finding a first feasible solution represents the first step for several MIP solvers. The Feasibility pump is a heuristic for finding feasible solutions to mixed integer...

Current generalizations of the central ideas of single-objective branch-and-bound to the multiobjective setting do not seem to follow their train of thought all the way. The present paper complements the various suggestions for generalizations of partial lower bounds and of overall upper bounds...

For a continuous multi-objective optimization problem, it is usually not a practical approach to compute all its nondominated points because there are infinitely many of them. For this reason, a typical approach is to compute an approximation of the nondominated set. A common technique for this...