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Solving NP-complete Problems with Metaheuristics

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 De Smet, Geoffrey

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Solving NP-complete Problems with Metaheuristics
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An Introduction to Tabu Search, Simulated Annealing and Late Acceptance
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199
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CC Attribution 2.0 Belgium:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Abstract
Some scientific research problems inherently suffer from an NP-complete problem. This session will explain several meta-heuristic algorithms which can handle such problems in reasonable time. This session will also do lightning introduction of OptaPlanner, an open source Apache licensed Java library, which implements those algorithms. Specifically, these algorithms will be explained: * First Fit * First Fit Decreasing * Hill Climbing * Tabu Search * Simulated Annealing * Late Acceptance