Tabu Search

Tabu search is a local search algorithm that tries to avoid converging to a local optimum by declaring some previously visited solutions or solution sub-structures as “tabu.” Solutions that are “tabu” must not be visited by the search, which therefore is less likely to get stuck or to drop into a cycle of resampling the same solutions again and again. We can consider Tabu search as a randomized local search (RLS) to which the tabu criterion is added.

Publications

• Thomas Weise (汤卫思), Xiao-Feng WANG (王晓峰), Qi QI (齐琪), Bin LI (李斌), and Ke TANG (唐珂): Automatically discovering clusters of algorithm and problem instance behaviors as well as their causes from experimental data, algorithm setups, and instance features. Applied Soft Computing Journal (ASOC), 73:366–382, December 2018.
  TSP, logistics, benchmarking, optimizationBenchmarking, ACO, EAs, local search, Tabu Search, more infos.
• Qi QI (齐琪), Thomas Weise (汤卫思), and Bin LI (李斌): Optimization Algorithm Behavior Modeling: A Study on the Traveling Salesman Problem. 10th International Conference on Advanced Computational Intelligence (ICACI'2018), March 29-31, 2018, Xiamen, Fujian, China, IEEE, pages 861-866.
  TSP, TSP Suite, logistics, benchmarking, Tabu Search, more infos.
• Dan XU (许丹), Thomas Weise (汤卫思), Yuezhong WU (吴越钟), Jörg Lässig, and Raymond Chiong: An Investigation of Hybrid Tabu Search for the Traveling Salesman Problem. 10th International Conference on Bio-Inspired Computing — Theories and Applications (BIC-TA'2015), September 25-28, 2015, Hefei, Anhui, China, Communications in Computer and Information Science, volume 562. Berlin/Heidelberg: Springer-Verlag, pages 523-537.
  TSP, TSP Suite, logistics, Tabu Search, local search, more infos.