Marianna De Santis

Quadratic Convex Reformulations for MultiObjective Binary Quadratic Programming

  • Marianna De Santis
  • Lucas Létocart
  • Yue Zhang
    • Categories (Mixed) Integer Nonlinear Programming, 0-1 Programming, Multi-Criteria Optimization Tags , , ,

    Multiobjective binary quadratic programming refers to optimization problems involving multiple quadratic – potentially non-convex – objective functions and a feasible set that includes binary constraints on the variables. In this paper, we extend the well-established Quadratic Convex Reformulation technique, originally developed for single-objective binary quadratic programs, to the multiobjective setting. We propose a branch-and-bound algorithm … Read more

    Designing sustainable diet plans by solving triobjective integer programs

  • Marianna De Santis
  • Alberto De Santis
  • Daniele Patria
    • Categories Applications - OR and Management Sciences, Multi-Criteria Optimization Tags , ,

    We present an algorithm for triobjective nonlinear integer programs that combines the epsilon-constrained method with available oracles for biobjective integer programs. We prove that our method is able to detect the nondominated set within a finite number of iterations. Specific strategies to avoid the detection of weakly nondominated points are devised. The method is then … Read more

    On Necessary Optimality Conditions for Sets of Points in Multiobjective Optimization

  • Andrea Cristofari
  • Marianna De Santis
  • Stefano Lucidi
    • Categories Multi-Criteria Optimization Tags , ,

    Taking inspiration from what is commonly done in single-objective optimization, most local algorithms proposed for multiobjective optimization extend the classical iterative scalar methods and produce sequences of points able to converge to single efficient points. Recently, a growing number of local algorithms that build sequences of sets has been devised, following the real nature of … Read more

    An algorithmic framework in the criterion space for bi-objective mixed integer linear problems

  • Lavinia Amorosi
  • Marianna De Santis
    • Categories (Mixed) Integer Linear Programming, Multi-Criteria Optimization Tags , ,

    We propose a criterion space search algorithm for bi-objective mixed integer linear programming problems. The Pareto frontier of these problems can have a complex structure, as it can include isolated points, open, half-open and closed line segments. Therefore, its exact detection is an achievable though hard computational task. Our algorithm works by alternating the resolution … Read more

    Using dual relaxations in multiobjective mixed-integer quadratic programming

  • Marianna De Santis
  • Gabriele Eichfelder
  • Daniele Patria
  • Leo Warnow
    • Categories (Mixed) Integer Nonlinear Programming, Multi-Criteria Optimization Tags , , ,

    We present a branch-and-bound method for multiobjective mixed-integer convex quadratic programs that computes a superset of efficient integer assignments and a coverage of the nondominated set. The method relies on outer approximations of the upper image set of continuous relaxations. These outer approximations are obtained addressing the dual formulations of specific subproblems where the values … Read more

    An oracle-based framework for robust combinatorial optimization

  • Enrico Bettiol
  • Christoph Buchheim
  • Marianna De Santis
  • Francesco Rinaldi
    • Categories Global Optimization, Robust Optimization Tags , ,

    We propose a general solution approach for min-max-robust counterparts of combinatorial optimization problems with uncertain linear objectives. We focus on the discrete scenario case, but our approach can be extended to other types of uncertainty sets such as polytopes or ellipsoids. Concerning the underlying certain problem,the algorithm is entirely oracle-based, i.e., our approach only requires … Read more

    Minimization over the l1-ball using an active-set non-monotone projected gradient

  • Andrea Cristofari
  • Marianna De Santis
  • Stefano Lucidi
  • Francesco Rinaldi
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization Tags , , ,

    The l1-ball is a nicely structured feasible set that is widely used in many fields (e.g., machine learning, statistics and signal analysis) to enforce some sparsity in the model solutions. In this paper, we devise an active-set strategy for efficiently dealing with minimization problems over the l1-ball and embed it into a tailored algorithmic scheme … Read more

    On the exactness of the eps-constraint method for bi-objective integer nonlinear programming

  • Marianna De Santis
  • Daniele Patria
    • Categories (Mixed) Integer Nonlinear Programming, Multi-Criteria Optimization Tags , , ,

    The eps-constraint method is a well-known scalarization technique used for multiobjective optimization. We explore how to properly define the step size parameter of the method in order to guarantee its exactness when dealing with problems having two nonlinear objective functions and integrality constraints on the variables. Under specific assumptions, we prove that the number of … Read more

    A Penalty Branch-and-Bound Method for Mixed-Binary Linear Complementarity Problems

  • Marianna De Santis
  • Sven de Vries
  • Martin Schmidt
  • Lukas Winkel
    • Categories (Mixed) Integer Nonlinear Programming, Branch and Cut Algorithms, Complementarity and Variational Inequalities Tags , , , ,

    Linear complementarity problems (LCPs) are an important modeling tool for many practically relevant situations but also have many important applications in mathematics itself. Although the continuous version of the problem is extremely well studied, much less is known about mixed-integer LCPs (MILCPs) in which some variables have to be integer-valued in a solution. In particular, … Read more

    Dealing with inequality constraints in large-scale semidefinite relaxations for graph coloring and maximum clique problems

  • Federico Battista
  • Marianna De Santis
    • Categories Combinatorial Optimization, Convex Optimization, Semi-definite Programming Tags , ,

    Semidefinite programs (SDPs) can be solved in polynomial time by interior point methods. However, when the dimension of the problem gets large, interior point methods become impractical in terms of both computational time and memory requirements. Certain first-order methods, such as Alternating Direction Methods of Multipliers (ADMMs), established as suitable algorithms to deal with large-scale … Read more