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Randomized local search (RLS) is maybe the simplest algorithm. It maintains one single best-so-far solution and in each step, it samples one new solution by applying the unary search operator to it. It will accept the new solution as the current solution if it is not worse. This search works already surprisingly well on a wide set of optimization problems. It can be viewed as the bottom line that any new metaheuristic must significantly outperform to be worth its salt. If we plug Frequency Fitness Assignment () into this algorithm, we obtain the .

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Plugging Frequency Fitness Assignment into Metaheuristics

12 minute read

Frequency Fitness Assignment () is a technique that fundamentally changes how (metaheuristic) optimization algorithms work. The goal of this post is to explore how this technique can be plugged into an existing algorithm. We first discuss optimization and the general pattern of metaheuristics in general. We then discuss the simplest local search algorithm – randomized local search, or for short. We plug FFA into this algorithm and obtain the . We finally list some properties of FRLS as well as some related works.

Publications

  • Rui ZHAO (赵睿), Zhize WU (吴志泽), Daan van den Berg, Matthias Thürer, Tianyu LIANG (梁天宇), Tan MING (檀明), and Thomas Weise (汤卫思): Randomized Local Search for Two-Dimensional Bin Packing and a Negative Result for Frequency Fitness Assignment. International Conference on Evolutionary Computation Theory and Applications (ECTA'2024), part of 16th International Joint Conference on Computational Intelligence (IJCCI'2024), November 20-22, 2024, Porto, Portugal, pages 15-26. Setúbal, Portugal: SciTePress.
  • Jiayang CHEN (陈嘉阳), Zhize WU (吴志泽), Sarah Louise Thomson, and Thomas Weise (汤卫思): Frequency Fitness Assignment: Optimization Without Bias for Good Solution Outperforms Randomized Local Search on the Quadratic Assignment Problem. International Conference on Evolutionary Computation Theory and Applications (ECTA'2024), part of 16th International Joint Conference on Computational Intelligence (IJCCI'2024), November 20-22, 2024, Porto, Portugal, pages 27-37. Setúbal, Portugal: SciTePress.
  • Tianyu LIANG (梁天宇), Zhize WU (吴志泽), Matthias Thürer, Markus Wagner, and Thomas Weise (汤卫思): Generating Small Instances with Interesting Features for the Traveling Salesperson Problem. International Conference on Evolutionary Computation Theory and Applications (ECTA'2024), part of 16th International Joint Conference on Computational Intelligence (IJCCI'2024), November 20-22, 2024, Porto, Portugal, pages 173-180. Setúbal, Portugal: SciTePress.
  • Xiang CAO (曹翔), Zhize WU (吴志泽), Daan van den Berg, and Thomas Weise (汤卫思): Randomized Local Search vs. NSGA-II vs. Frequency Fitness Assignment on The Traveling Tournament Problem. International Conference on Evolutionary Computation Theory and Applications (ECTA'2024), part of 16th International Joint Conference on Computational Intelligence (IJCCI'2024), November 20-22, 2024, Porto, Portugal, pages 38-49. Setúbal, Portugal: SciTePress.
  • Sarah Louise Thomson, Gabriela Ochoa, Daan van den Berg, Tianyu LIANG (梁天宇), and Thomas Weise (汤卫思): Entropy, Search Trajectories, and Explainability for Frequency Fitness Assignment. 18th International Conference on Parallel Problem Solving from Nature (PPSN XVIII), September 14-18, 2024, Hagenberg, Austria, pages 377-392. Lecture Notes in Computer Science (LNCS), volume 15148. Berlin/Heidelberg, Germany: Springer.
  • Tianyu LIANG (梁天宇), Zhize WU (吴志泽), Jörg Lässig, Daan van den Berg, Sarah Louise Thomson, and Thomas Weise (汤卫思): Addressing the Traveling Salesperson Problem with Frequency Fitness Assignment and Hybrid Algorithms. Soft Computing 28(17-18):9495-9508. September 2024.
  • Rui ZHAO (赵睿), Tianyu LIANG (梁天宇), Zhize WU (吴志泽), Daan van den Berg, Matthias Thürer, and Thomas Weise (汤卫思): Randomized Local Search on the 2D Rectangular Bin Packing Problem with Item Rotation. Genetic and Evolutionary Computation Conference (GECCO'2024) Companion, July 14-18, 2024, Melbourne, VIC, Australia, pages 235-238. New York, NY, USA: ACM.
  • Tianyu LIANG (梁天宇), Zhize WU (吴志泽), Jörg Lässig, Daan van den Berg, and Thomas Weise (汤卫思): Solving the Traveling Salesperson Problem using Frequency Fitness Assignment. IEEE Symposium on Foundations of Computational Intelligence (IEEE FOCI'2022), part of the IEEE Symposium Series on Computational Intelligence (SSCI'2022), December 4-7, 2022, Singapore. IEEE.