Global equilibrium search algorithms for combinatorial optimization problems

  • Authors:

  • Oleg Shylo;Dmytro Korenkevych;Panos M. Pardalos

  • Affiliations:

  • Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, PA;Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL;Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA,Laboratory of Algorithms and Technologies for Network Analysis (LATNA), National Research University H ...

  • Venue:
  • PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
  • Year:
  • 2012

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Abstract

Global Equilibrium Search (GES) is a meta-heuristic framework that shares similar ideas with the simulated annealing method. GES accumulates a compact set of information about the search space to generate promising initial solutions for the techniques that require a starting solution, such as the simple local search method. GES has been successful for many classic discrete optimization problems: the unconstrained quadratic programming problem, the maximum satisfiability problem, the max-cut problem, the multidimensional knapsack problem and the job-shop scheduling problem. GES provides state-of-the-art performance on all of these domains when compared to the current best known algorithms from the literature. GES algorithm can be naturally extended for parallel computing as it performs search simultaneously in distinct areas of the solution space. In this talk, we provide an overview of Global Equilibrium Search and discuss some successful applications.