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2008
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A feasibility-preserving local search operator for constrained discrete optimization problems

8 years 8 months ago
A feasibility-preserving local search operator for constrained discrete optimization problems
Abstract— Meta-heuristic optimization approaches are commonly applied to many discrete optimization problems. Many of these optimization approaches are based on a local search operator like, e.g., the mutate or neighbor operator that are used in Evolution Strategies or Simulated Annealing, respectively. However, the straightforward implementations of these operators tend to deliver infeasible solutions in constrained optimization problems leading to a poor convergence. In this paper, a novel scheme for a local search operator for discrete constrained optimization problems is presented. By using a sophisticated methodology incorporating a backtracking-based ILP solver, the local search operator preserves the feasibility also on hard constrained problems. In detail, an implementation of the local serach operator as a feasibility-preserving mutate and neighbor operator is presented. To validate the usability of this approach, scalable discrete constrained testcases are introduced that a...
Martin Lukasiewycz, Michael Glaß, Christian
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where CEC
Authors Martin Lukasiewycz, Michael Glaß, Christian Haubelt, Jürgen Teich
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