Integrality gap minimization heuristics for binary mixed integer nonlinear programming

Melo, Wendel; Fampa, Marcia; Raupp, Fernanda M. P.

doi:10.1007/s10898-018-0623-4

Cited by 10 publications

(2 citation statements)

References 29 publications

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“…In the result's discussion, the author omitted the data from benchmarks where one of their algorithms cannot find feasible solutions in less than 50.000 seconds. Melo, Fampa, and Raupp [8] developed another work that has a similar approach.…”

Section: Introductionmentioning

confidence: 99%

On the statistical evaluation of algorithmic's computational experimentation with infeasible solutions

Carvalho

2019

Information Processing Letters

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The experimental evaluation of algorithms results in a large set of data which generally do not follow a normal distribution or are not heteroscedastic. Besides, some of its entries may be missing, due to the inability of an algorithm to find a feasible solution until a time limit is met. Those characteristics restrict the statistical evaluation of computational experiments. This work proposes a bi-objective lexicographical ranking scheme to evaluate datasets with such characteristics. The output ranking can be used as input to any desired statistical test. We used the proposed ranking scheme to assess the results obtained by the Iterative Rounding heuristic (IR). A Friedman's test and a subsequent post-hoc test carried out on the ranked data demonstrated that IR performed significantly better than the Feasibility Pump heuristic when solving 152 benchmark problems of Nonconvex Mixed-Integer Nonlinear Problems. However, is also showed that the RECIPE heuristic was significantly better than IR when solving the same benchmark problems.

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Section: Introductionmentioning

confidence: 99%

On the statistical evaluation of algorithmic's computational experimentation with infeasible solutions

Carvalho

2019

Information Processing Letters

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“…-The subject of the paper [4] by Sonia Cafieri and Claudia D'Ambrosio consists of using feasibility pump heuristics for the problem of aircraft conflict avoidance arising in air traffic management; -M. Fernanda P. Costa, Ana Maria A.C. Rocha and Edite M.G.P. Fernandes investigate in [5] the use of a filter methodology in the DIRECT method to assure convergence in nonconvex constrained global optimization problems; -The paper [6] by Angelo Lucia, Peter A. DiMaggio and Diego Alonso-Martinez considers a new approach to metabolic network analysis using a Nash Equilibrium formulation; -Immanuel M. Bomze, Vaithilingam Jeyakumar and Guoyin Li in their paper [7] guarantee exact copositive and Lagrangian relaxations to extended trust region problems with one or two balls; -The paper [8] by Jan Kronqvist, Andreas Lundel and Tapio Westerlund discusses reformulations for utilizing separability when solving convex mixed-integer nonlinear programming problems; -Two feasibility heuristics based on the integrality gap minimization for binary mixedinteger nonlinear programming are discussed in the paper [9] by Wendel Melo, Marcia Fampa and Fernanda Raupp; -A sampling-based exact algorithm for the solution of the minimax diameter clustering problem is proposed in the paper [10] by Daniel Aloise and Claudio Contardo; -J. J. Moreno, Gloria Ortega, Ernestas Filatovas, J. A. Martínez and E. M. Garzón in their paper [11] discuss the improvement of the performance and energy of non-dominated sorting for evolutionary multiobjective optimization on GPU/CPU platforms.…”

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confidence: 99%

Preface to the Special Issue “GOW’16”

2018

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This special issue of the Journal of Global Optimization consists of papers presented at the XIII Global Optimization Workshop (GOW'16), which took place on September 4th-8th, 2016, at the University of Minho, in Braga, Portugal. This workshop attracted 54 participants from 14 countries and the scientific program contained one invited talk by Professor Panos Pardalos and 47 contributed talks. These global optimization workshops have been held since 1985 and more recently every two years. This special issue mainly focuses on deterministic methods and heuristics for global optimization. Problems with continuous as well as with integer variables are discussed. Some stochastic algorithms are also investigated. The papers were reviewed in the usual process and eleven papers were accepted for publication in this special issue. Below we give a brief presentation of the included papers.

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Modified Extended Cutting Plane Algorithm for Mixed Integer Nonlinear Programming

Melo

Fampa

Raupp

2019

Advances in Intelligent Systems and Computing

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Integrality gap minimization heuristics for binary mixed integer nonlinear programming

Cited by 10 publications

References 29 publications

On the statistical evaluation of algorithmic's computational experimentation with infeasible solutions

On the statistical evaluation of algorithmic's computational experimentation with infeasible solutions

Preface to the Special Issue “GOW’16”

Modified Extended Cutting Plane Algorithm for Mixed Integer Nonlinear Programming

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