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Doctoral Thesis (Japanese)

Tomoaki Takagi: Pareto Front Estimation for Multi-Objective Decision-Making and Supervised/Unsupervised Multi-Objective Optimization, The University of Electro-Communications, March 2023. DOI.

Journal Papers

  1. Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: A Multi-objective Evolutionary Algorithm Using Weight Vector Arrangement Based on Pareto Front Estimation, Transaction of the Japanese Society for Evolutionary Computation (Japanese), Vol. 12, No. 2, pp. 45–60, 2021. DOI, Code. Best Papar Award.
  2. Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Directional Pareto Front and Its Estimation to Encourage Multi-Objective Decision-Making, IEEE Access, Vol. 11, pp. 20619–20634, 2023. DOI.

Conference Papers (First Author)

  1. Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: A Distribution Control of Weight Vector Set for Multi-objective Evolutionary Algorithms, Proc. of the Bio-inspired Information and Communication Technologies (BICT2019), Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST), Vol. 289, Springer, Cham, pp. 70–80, 2019. DOI, Code.
  2. Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Incremental Lattice Design of Weight Vector Set, Proc. of ACM Genetic and Evolutionary Computation Conference (GECCO2020), pp. 1486–1494, 2020. DOI, Code.
  3. Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Non-dominated Solution Sampling Using Environmental Selection in EMO algorithms, Proc. of IEEE Congress on Evolutionary Computation (CEC2020), pp. 1–9, 2020. DOI.
  4. Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Pareto Front Estimation Using Unit Hyperplane, Proc. of The 11th Edition of International Conference Series on Evolutionary Multi-Criterion Optimization (EMO2021), Lecture Notes in Computer Science (LNCS), Vol. 12654, Springer, Cham, pp. 126–138, 2021. DOI, Code.
  5. Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Weight Vector Arrangement Using Virtual Objective Vectors in Decomposition-based MOEA, Proc. of IEEE Congress on Evolutionary Computation (CEC2021), pp. 1462–1469, 2021. DOI, Code.
  6. Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Supervised Multi-objective Optimization Algorithm Using Estimation, Proc. of IEEE Congress on Evolutionary Computation (CEC2022), pp. 1–8, 2022. DOI, Code.
  7. Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling, Proc. of The 12th Edition of International Conference Series on Evolutionary Multi-Criterion Optimization (EMO2023), Lecture Notes in Computer Science (LNCS), Vol. 13970, Springer, Cham, pp. 218–230, 2023. DOI, Code.

Conference Papers (Second Author)

  1. Kensuke Kano, Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Preliminary Study of Adaptive Grid-based Decomposition on Many-objective Evolutionary Optimization, Proc. of ACM Genetic and Evolutionary Computation Conference (GECCO2020), pp. 1373–1380, 2020.
  2. Kohei Yamamoto, Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Visual Mapping of Multi-objective Optimization Problems and Evolutionary Algorithms, Proc. of ACM Genetic and Evolutionary Computation Conference (GECCO2020), pp. 1872–1879, 2020.
  3. Shio Kawakami, Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: Distance Minimization Problems for Multi-factorial Evolutionary Optimization Benchmarking, Proc. of The 20th International Conference on Hybrid Intelligent Systems (HIS2020), Advances in Intelligent Systems and Computing, Vol. 1375, Springer, Cham, pp. 710–719, 2020.
  4. Naru Okumura, Tomoaki Takagi, Yoshihiro Ohta, and Hiroyuki Sato: Pareto Front Upconvert on Multi-objective Building Facility Control Optimization, Proc. of ACM Genetic and Evolutionary Computation Conference (GECCO2023), pp. 1963–1971, 2023.

Conference Papers (NO DOI)

  1. Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: A Preliminary Study on Weight Vector Distribution Control Based on Intermediate Objective Value, Proc. of 2018 JPNSEC International Workshop on Evolutionary Computation, pp. 20–26, 2018.
  2. Ryo Kumagai, Tomoaki Takagi, Keiki Takadama, and Hiroyuki Sato: A Study on Multi-objective Evolutionary Stage Generation Using MarioGAN, Proc. of The 7th UEC Seminar in ASEAN, 2020 and The 2nd ASEAN-UEC Workshop on Energy and AI, pp. 63–64, 2020. Young Researcher Encouragement Award.
  3. Kensuke Kano, Tomoaki Takagi, Shoichiro Tanaka, Keiki Takadama, and Hiroyuki Sato: Variable Elite Population in Grid-based Multi-objective Evolutionary Optimization, Proc. of The 3rd ASEAN-UEC Workshop on Informatics and Engineering for SDGs, 2 pages, 2021.
  4. Kosuke Kikawada, Tomoaki Takagi, Naru Okumura, Keiki Takadama, and Hiroyuki Sato: A Preliminary Study on Ensemble Pareto Front Estimation, Proc. of The 5th ASEAN-UEC Workshop on Informatics and Engineering, pp. 18–19, 2023.
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