{"id":829,"date":"2023-06-06T15:20:46","date_gmt":"2023-06-06T06:20:46","guid":{"rendered":"http:\/\/forest.sys.okayama-u.ac.jp\/nishilab\/?page_id=829"},"modified":"2026-02-25T12:01:59","modified_gmt":"2026-02-25T03:01:59","slug":"recent_publication","status":"publish","type":"page","link":"https:\/\/isopt.is.ritsumei.ac.jp\/nishilab\/?page_id=829","title":{"rendered":"\u6700\u65b0\u306e\u7814\u7a76\u6210\u679c"},"content":{"rendered":"

2025\u5e74<\/p>\n

\u30b8\u30e3\u30fc\u30ca\u30eb\u8ad6\u6587<\/p>\n

    \n
  1. Tomoya Kawabe, Tatsushi Nishi, Ziang Liu, Tomofuji Fujiwara, Surrogate-Assisted Motion Planning and Layout Design of Robotic Cellular Manufacturing Systems, Engineering Applications of Artificial Intelligence, Vol. 150, 110530, DOI: https:\/\/doi.org\/10.1016\/j.engappai.2025.110530<\/a><\/li>\n
  2. Yusuke Nomura, Ziang Liu, Tatsushi Nishi, Deep Reinforcement Learning for Dynamic Pricing and Ordering Policies in Perishable Inventory Management, Applied Sciences, Vol. 15, No. 5, 2421, https:\/\/doi.org\/10.3390\/app15052421<\/a><\/li>\n
  3. Md. Kaimujjaman, Tatsushi Nishi, Tomofumi Fujiwara, Hierarchical Optimization of Robotic Placement, Motion Planning, and Posture for Multi-Target Manipulation, Applied Sciences, Vol. 15, 11941, https:\/\/doi.org\/10.3390\/app152211941<\/a><\/li>\n
  4. Md. Kaimujjaman, Tatsushi Nishi, Ziang Liu, Tomofumi Fujiwara, Motion and Path Planning of Mobile Robot for Autonomous Navigation with A* and Q-learning Algorithms, Transactions of the Institute of Systems, Control and Information Engineers, Vol. 30, No. 2, pp. 21-29, 2026.<\/li>\n<\/ol>\n

    \u56fd\u969b\u4f1a\u8b70\u8ad6\u6587<\/p>\n

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    1. Mst Sumaya Akter, Tatsushi Nishi, Design of a Robust Optimization Model Using Mixed-Integer Programming for a Multi-Objective, Multi-Plant Supply Chain Network Under Demand Uncertainty, Presented at International Symposium on Scheduling 2025.<\/li>\n
    2. Radwa Ali, Zhengtao Hu, Takuya Kiyokawa, Weiwei Wan, Tatsushi Nishi, Kensuke Harada, Task and Grasp Constrained 3D Robotic Work-Cell Layout Planning, IEEE International Conference on Automation Science and Engineering,\u00a0 pp. 2355-2362, DOI:https:\/\/doi.org\/10.1109\/CASE58245.2025.11164140<\/a><\/li>\n
    3. Mst Sumaya Akter, Tatsushi Nishi, Ziang Liu, A Multi-Period Multi-Objective Model for Sustainable Supply Chain Optimization Using MILP Framework, IFIP Advances in Information and Communication Technology, vol. 765, pp. 303-319, 2026. DOI:https:\/\/doi.org\/10.1007\/978-3-032-03534-9_21<\/a><\/li>\n
    4. Kohei Toda, Tatsushi Nishi, Ziang Liu, Local Explanation Method for Ordering Policy in Perishable Inventory Management Problem Using LLM and LIME, IFIP Advances in Information and Communication Technology, vol. 765, pp. 289-302, 2026. DOI: https:\/\/doi.org\/0.1007\/978-3-032-03534-9_20<\/a><\/li>\n
    5. Md Kaimujjaman, Tatsushi Nishi, Cooperative Multi-Robot Pick-and-Place Systems via Layout and Motion Optimization Using Evolutionary Algorithms, Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management 2025<\/li>\n
    6. Mst Sumaya Akter, Tatsushi Nishi, Robust Optimization Model for Multi-Echelon Supply Chain Network Under Demand and Supply Uncertainty, Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management 2025<\/li>\n<\/ol>\n

      \u53e3\u982d\u767a\u8868<\/p>\n

        \n
      1. \u738b\u535a\u777f, \u897f \u7adc\u5fd7, \u5289 \u5b50\u6602, \u85e4\u539f \u59cb\u53f2, \u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u306b\u57fa\u3065\u304f\u95a2\u7bc0\u7a7a\u9593\u5236\u5fa1, \u7b2c69\u56de\u30b7\u30b9\u30c6\u30e0\u5236\u5fa1\u60c5\u5831\u5b66\u4f1a\u7814\u7a76\u767a\u8868\u8b1b\u6f14\u4f1a, 2025.5<\/li>\n
      2. \u2f2d\u672c\u7965\u54c9, \u2ec4 \u2eef\u5fd7\uff0c\u85e4\u539f \u59cb\u53f2\uff0c\u5289 \u2f26\u6602, \u30ed\u30dc\u30c3\u30c8\u30a2\u30fc\u30e0\u3092\u2f64\u3044\u305f\u54c1\u51fa\u3057\u52d5\u4f5c\u306b\u304a\u3051\u308b\u74b0\u5883\u8a8d\u8b58\u3092\u963b\u5bb3\u3057\u306a\u3044\u2f83\u52d5\u4f38\u7e2e\u5f0f\u30b0\u30ea\u30c3\u30d1\u306e\u8a2d\u8a08, \u7b2c69\u56de\u30b7\u30b9\u30c6\u30e0\u5236\u5fa1\u60c5\u5831\u5b66\u4f1a\u7814\u7a76\u767a\u8868\u8b1b\u6f14\u4f1a, 2025.5<\/li>\n
      3. \u6e80\u5712\u4fee\u592a\u90ce\uff0c\u2ec4 \u2eef\u5fd7\uff0c\u85e4\u539f \u59cb\u53f2\uff0c\u5289 \u2f26\u6602, \u8a18\u53f7\u5217\u2f0a\u2f12\u3092\u2f64\u3044\u305f\u30bf\u30b9\u30af\u3068\u52d5\u4f5c\u8a08\u753b\u306e\u540c\u6642\u8a08\u753b\u6cd5\u306e\u7523\u696d\u2f64\u30ed\u30dc\u30c3\u30c8\u306b\u3088\u308b\u54c1\u51fa\u3057\u4f5c\u696d\u3078\u306e\u9069\u2f64, \u7b2c69\u56de\u30b7\u30b9\u30c6\u30e0\u5236\u5fa1\u60c5\u5831\u5b66\u4f1a\u7814\u7a76\u767a\u8868\u8b1b\u6f14\u4f1a, 2025.5<\/li>\n
      4. \u9234\u2f4a \u2fd3\u4e4b\u4ecb\uff0c\u2ec4 \u2eef\u5fd7\uff0c\u85e4\u539f \u59cb\u53f2\uff0c\u5289 \u2f26\u6602, \u30b5\u30ed\u30b2\u30fc\u30c8\u30e2\u30c7\u30eb\u3092\u2f64\u3044\u305f\u5358\u2f00\u30ed\u30dc\u30c3\u30c8\u30a2\u30fc\u30e0\u306e\u914d\u7f6e\u8a08\u753b\u3068\u52d5\u4f5c\u8a08\u753b\u306e\u540c\u6642\u6700\u9069\u5316, \u7b2c69\u56de\u30b7\u30b9\u30c6\u30e0\u5236\u5fa1\u60c5\u5831\u5b66\u4f1a\u7814\u7a76\u767a\u8868\u8b1b\u6f14\u4f1a, 2025.5<\/li>\n
      5. \u738b \u535a\u777f, \u897f \u7adc\u5fd7, \u5289 \u5b50\u6602, \u85e4\u539f \u59cb\u53f2, \u6df1\u5c64\u5f37\u5316\u5b66\u7fd2\u306b\u57fa\u3065\u304f6\u8ef8\u30ed\u30dc\u30c3\u30c8\u30a2\u30fc\u30e0\u306e\u7d71\u5408\u5236\u5fa1, \u7b2c68\u56de\u81ea\u52d5\u5236\u5fa1\u9023\u5408\u8b1b\u6f14\u4f1a\u8b1b\u6f14\u8ad6\u6587\u96c6, 2025.11<\/li>\n
      6. \u4e09\u4e45 \u5c1a\u54c9, \u897f \u7adc\u5fd7, \u5289 \u5b50\u6602, \u85e4\u539f \u59cb\u53f2, \u5b8c\u4e86\u6642\u9593\u4e88\u6e2c\u306b\u57fa\u3065\u304f\u52d5\u7684\u74b0\u5883\u306b\u304a\u3051\u308b\u8907\u6570\u53f0\u79fb\u52d5\u30ed\u30dc\u30c3\u30c8\u306e\u30bf\u30b9\u30af\u5272\u5f53\u3068\u7d4c\u8def\u8a08\u753b\u6cd5, \u7b2c68\u56de\u81ea\u52d5\u5236\u5fa1\u9023\u5408\u8b1b\u6f14\u4f1a\u8b1b\u6f14\u8ad6\u6587\u96c6, 2025.11<\/li>\n
      7. \u5c71\u672c \u7965\u54c9, \u4e0a\u91ce \u96bc, \u85e4\u539f \u59cb\u53f2, \u897f \u7adc\u5fd7, \u30ed\u30dc\u30c3\u30c8\u30a2\u30fc\u30e0\u3092\u7528\u3044\u305f\u54c1\u51fa\u3057\u4f5c\u696d\u3068\u81ea\u52d5\u4f38\u7e2e\u30b0\u30ea\u30c3\u30d1\u306e\u52d5\u4f5c\u306e\u9023\u643a, \u7b2c26\u56de\u8a08\u6e2c\u81ea\u52d5\u5236\u5fa1\u5b66\u4f1a\u30b7\u30b9\u30c6\u30e0\u30a4\u30f3\u30c6\u30b0\u30ec\u30fc\u30b7\u30e7\u30f3\u90e8\u9580\u8b1b\u6f14\u4f1a, 2025.12<\/li>\n
      8. \u6751\u4e0a \u6b66\u7460, \u85e4\u539f \u59cb\u53f2, \u897f \u7adc\u5fd7, \u79fb\u52d5\u30de\u30cb\u30d4\u30e5\u30ec\u30fc\u30bf\u306b\u3088\u308b\u54c1\u51fa\u52d5\u4f5c\u8a08\u753b\u306e\u305f\u3081\u306e\u8ee2\u5012\u3057\u306a\u3044\u52d5\u4f5c\u8a08\u753b\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u3068\u5b9f\u6a5f\u3067\u306e\u691c\u8a3c, \u7b2c26\u56de\u8a08\u6e2c\u81ea\u52d5\u5236\u5fa1\u5b66\u4f1a\u30b7\u30b9\u30c6\u30e0\u30a4\u30f3\u30c6\u30b0\u30ec\u30fc\u30b7\u30e7\u30f3\u90e8\u9580\u8b1b\u6f14\u4f1a, 2025.12<\/li>\n<\/ol>\n

        2024\u5e74<\/p>\n

        \u66f8\u7c4d<\/p>\n

          \n
        1. \u00a0Michiko Matsuda, Tatsushi Nishi, Enterprise E-Profiles for Construction of a Collaborative Network in Cyberspace, Enterprise Interoperability X, Proceedings of the I-ESA Conferences, vol 11. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-031-24771-2_7<\/li>\n<\/ol>\n

          \u30b8\u30e3\u30fc\u30ca\u30eb\u8ad6\u6587<\/p>\n

            \n
          1. Ziang Liu, Tatsushi Nishi, Surrogate-Assisted Evolutionary Optimization for Perishable Inventory Management in Multi-Echelon Distribution Systems, Expert Systems with Applications, 122179, 2024. DOI: https:\/\/doi.org\/10.1007\/s40747-023-01179-0<\/a><\/li>\n
          2. Shinya Korekane, Tatsushi Nishi, Kevin Tierney, Ziang Liu, Neural network assisted branch and bound algorithm for dynamic berth allocation problems. European Journal of Operational Research, Vol. 319, No. 2, pp. 531-542, DOI: https:\/\/doi.org\/10.1016\/j.ejor.2024.06.040<\/a><\/li>\n
          3. \u798f\u5cf6\u6602\u4e4b\u4ecb\uff0c\u897f\u7adc\u5fd7\uff0c\u5289\u5b50\u6602\uff0c\u85e4\u539f\u59cb\u53f2\uff0cDeep Q-Network\u3068\u30b0\u30e9\u30d5\u63a2\u7d22\u3092\u7d44\u307f\u5408\u308f\u305b\u305f\u8907\u6570\u53f0\u79fb\u52d5\u30ed\u30dc\u30c3\u30c8\u306e\u7d4c\u8def\u8a08\u753b\u6cd5, \u30b7\u30b9\u30c6\u30e0\u5236\u5fa1\u60c5\u5831\u5b66\u4f1a\u8ad6\u6587\u8a8c, Vol. 37, No. 8, pp. 207-215, 2024.<\/li>\n
          4. \u85e4\u539f\u59cb\u53f2\uff0c\u897f\u7adc\u5fd7, \u5289\u5b50\u6602, \u7c92\u5b50\u7fa4\u6700\u9069\u5316\u306b\u3088\u308b\u7523\u696d\u7528\u30b9\u30ab\u30e9\u578b\u30ed\u30dc\u30c3\u30c8\u306e\u7701\u30a8\u30cd\u30eb\u30ae\u30fc\u52d5\u4f5c\u8a08\u753b\u306e\u691c\u8a0e, \u30b7\u30b9\u30c6\u30e0\u5236\u5fa1\u60c5\u5831\u5b66\u4f1a\u8ad6\u6587\u8a8c, Vol. 37, No. 11, pp.\u00a0 283-290, 2024.<\/li>\n
          5. Tatsushi Nishi, Hidefumi Kurakado, Ziang Liu, Resource Constrained Project Scheduling Formulation for Optimization of Product Input Sequence and Workforce Scheduling for Multi-Stage Multi-Product Cellular Production Lines, Journal of Advanced Mechanical Design, Systems and Manufacturing, Vol. 18, No. 5, JAMDSM0062, 2024. DOI: https:\/\/doi.org\/10.1299\/jamdsm.2024jamdsm0062<\/a><\/li>\n
          6. Tatsushi Nishi, Naoto Debuchi, Ziang Liu, Distributed Optimization Algorithm for Multi-Agent Optimization Problems Using Consensus Control, Journal of Advanced Mechanical Design, Systems and Manufacturing, Vol. 18, No. 5, JAMDSM0073, DOI: https:\/\/doi.org\/10.1299\/jamdsm.2024jamdsm0073<\/a>.<\/li>\n
          7. Ziang Liu, Tomoya Kawabe, Tatsushi Nishi, Shun Ito, Tomofumi Fujiwara, Surrogate-Assisted Multi-Objective Optimization for Simultaneous Three-Dimensional Packing and Motion Planning Problems Using the Sequence-Triple Representation, Applied Artificial Intelligence, Vol. 38, No. 1, 2398895, 2024. DOI: https:\/\/doi.org\/10.1080\/08839514.2024.2398895<\/a>.<\/li>\n<\/ol>\n

            \u56fd\u969b\u4f1a\u8b70\u8ad6\u6587<\/p>\n

              \n
            1. Md Kaimujjaman, Tatsushi Nishi, Tomofumi Fujiwara, Ziang Liu, Designing a Mobile Manipulator and Motion Planning for Autonomous Navigation With A* and Q-Learning Algorithms, International Symposium on Flexible Automation 2024, Seattle, U.S.A., July 2024.<\/li>\n
            2. Ziang Liu, Tatsushi Nishi, Surrogate-Assisted Evolutionary Computation for Distributed Simulation-Based Inventory Optimization in Serial Supply Chains, IEEE Congress on Evolutionary Computation, Proceedings of CEC 2024.<\/li>\n
            3. Tomoya Kawabe, Tatsushi Nishi, Ziang Liu, Tomofumi Fujiwara, Task Planning for Robot Manipulator Using Natural Language Task Input with Large Language Models, IEEE International Conference on Automation Science and Engineering 2024, Bari, Italy, August 2024.<\/li>\n
            4. Hidefumi Kurakado, Tatsushi Nishi, Ziang Liu, Data-Driven Scheduling of Cellular Manufacturing Systems using Process Mining with Petri Nets, IFIP Advances in Information and Communication Technology, pp. 17-28, 2024, presented at Advance in Production Management Systems 2024 (APMS 2024), September 2024.<\/li>\n
            5. Naoya Mikyu, Tatsushi Nishi, Ziang Liu, Tomofumi Fujiwara, Three-Dimensional Bin Packing Problems with the Operating Time of a Robot Manipulator, IFIP Advances in Information and Communication Technology, pp. 44-60, Advance in Production Management Systems 2024 (APMS 2024), September 2024.<\/li>\n<\/ol>\n

              2023\u5e74<\/p>\n

              \u66f8\u7c4d<\/p>\n

                \n
              1. \u00a0Tatsushi Nishi, Co-evolutionary Decision-Making Modeling Via Integration of Machine Learning and Optimization, Chapter 8, Kaihara et al. ed. Innovative Systems Approach for Facilitating Smarter World, \u00a0 ISBN 978-981-19-7775-6 (2023).<\/li>\n<\/ol>\n

                \u89e3\u8aac\u8ad6\u6587<\/p>\n

                  \n
                1. Md Moktadir Alam and Tatsushi Nishi, Application of Artificial Intelligence and Machine Learning in Sampling-Based Motion Planning Algorithms for Industrial Robots, Systems, Control and Information, Vol. 67, No. 3, pp. 116-120.<\/li>\n<\/ol>\n

                  \u30b8\u30e3\u30fc\u30ca\u30eb\u8ad6\u6587<\/p>\n

                    \n
                  1. Tomoya Kawabe, Tatsushi Nishi, Ziang Liu, Flexible Route Planning for Multiple Mobile Robots by Combining Q\u2013Learning and Graph Search Algorithm, Applied Sciences, Vol. 13, No. 3, 1879, 2023. DOI: https:\/\/doi.org\/10.3390\/app13031879<\/a><\/li>\n
                  2. K. Nishida and T. Nishi, Dynamic Optimization of Conflict-Free Routing of Automated Guided Vehicles for Just-in-Time Delivery, IEEE Transactions on Automation Science and Engineering<\/em>, Vol. 20, No. 3, 2023. DOI: https:\/\/doi.org\/10.1109\/TASE.2022.3194082<\/a><\/li>\n
                  3. Ziang Liu, Tatsushi Nishi, Data-Driven Evolutionary Computation for Service Constrained Inventory Optimization in Multi-Echelon Supply Chains, Complex & Intelligent Systems, 2023. DOI: https:\/\/doi.org\/10.1007\/s40747-023-01179-0<\/a><\/li>\n
                  4. Md Moktadir Alam, Tatsushi Nishi, Ziang Liu, Tomofumi Fujiwara, A Novel Sampling-Based Optimal Motion Planning Algorithm for Energy-Efficient Robotic Pick and Place, Energies, Vol. 16, No. 19, 6910: https:\/\/doi.org\/10.3390\/en16196910<\/a><\/li>\n
                  5. Yu Nishihata, Ziang Liu, Tatsushi Nishi, Evolutionary-Game-Theory-Based Epidemiological Model for Prediction of Infections with Application to Demand Forecasting in Pharmaceutical Inventory Management Problems, Applied Sciences, Vol. 13, No. 20, 11308,\u00a0 https:\/\/doi.org\/10.3390\/app132011308<\/a><\/li>\n<\/ol>\n

                    \u56fd\u969b\u4f1a\u8b70\u8ad6\u6587<\/p>\n

                      \n
                    1. Naoto Debuchi, Tatsushi Nishi, Ziang Liu, Distributed Optimization for Unit Commitment Problem Using Subgradient and Consensus Control, Proceedings of International Symposium on Scheduling 2023, pp. 66-69, 2023.<\/li>\n
                    2. Hidefumi Kurakado, Tatsushi Nishi, Ziang Liu, RCPSP Formulation of the Optimization of Product Input Sequence and Workforce Scheduling for Multi-Stage, Multi-Item Cell Production Lines, Proceedings of International Symposium on Scheduling 2023, pp. 110-114, 2023.<\/li>\n
                    3. Ziang Liu, Reimon Shirakashi, Ryuichi Kamiebisu, Tatsushi Nishi, Michiko Matsuda, Simulation-Based Optimization Using Virtual Supply Chain Structured by the Configuration Platform, Proceedings of IFAC World Congress 2023, pp. 8487-8491, 2023.<\/li>\n
                    4. Tomoya Kawabe, Tatsushi Nishi, Ziang Liu, Tomofumi Fujiwara, Symbolic Sequence Optimization Approach for Task and Motion Planning of Robot Manipulators, Proceedings of IEEE International Conference on Automation Science and Engineering, 2023.<\/li>\n
                    5. Konosuke Fukushima, Tatsushi Nishi, Ziang Liu, A Combined Deep Q-Network and Graph Search for Three Dimensional Route Planning Problems for Multiple Mobile Robots, Proceedings of IEEE International Conference on Automation Science and Engineering, 2023.<\/li>\n
                    6. Kengo Hara, Tatsushi Nishi, Ziang Liu, Tomofumi Fujiwara, Collision-Free Motion Planning for Multiple Robot Arms by Combining Deep Q-Network and Graph Search Algorithm, Proceedings of IEEE International Conference on Automation Science and Engineering, 2023.<\/li>\n
                    7. Jun Nakao, Tatsushi Nishi, Ziang Liu, Robust Optimization for Bilevel Production Planning Problems under Customer\u2019s Uncertainties, Proceedings of IEEE International Conference on Systems, Man and Cybernetics, 2023.<\/li>\n
                    8. Ziang Liu and Tatsushi Nishi, Inventory Control with Lateral Transshipment Using Proximal Policy Optimization, Proceedings of 5th<\/sup> International Conference on Data-driven Optimization of Complex Systems, 2023.<\/li>\n
                    9. Ziang Liu, Shun Ito, Tomoya Kawabe, Tatsushi Nishi, Tomofumi Fujiwara, Multi-objective Optimization for Three-dimensional Packing Problem Using the Sequence-triple Representation with Robot Motion Planning, Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management 2023.<\/li>\n
                    10. Tatsushi Nishi, Masaya Shiraga, Ziang Liu, Tomofumi Fujiwara, Motion Planning of Industrial Robot by Data-driven Optimization Using Petri Nets, Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management 2023.<\/li>\n
                    11. Yusuke Nomura, Ziang Liu, Tatsushi Nishi, Deep Reinforcement Learning for Perishable Inventory Optimization Problem, Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management 2023.<\/li>\n<\/ol>\n

                      2022\u5e74<\/p>\n

                      \u30b8\u30e3\u30fc\u30ca\u30eb\u8ad6\u6587<\/p>\n

                        \n
                      1. \u00a0\u6d45\u6cbc\u5016\u5e73, \u897f\u7adc\u5fd7, \u5165\u51fa\u529b\u30c7\u30fc\u30bf\u3092\u7528\u3044\u305f\u591a\u76ee\u7684\u30b9\u30b1\u30b8\u30e5\u30fc\u30ea\u30f3\u30b0\u554f\u984c\u306e\u91cd\u307f\u4fc2\u6570\u63a8\u5b9a, \u30b7\u30b9\u30c6\u30e0\u5236\u5fa1\u60c5\u5831\u5b66\u4f1a\u8ad6\u6587\u8a8c, Vol. 35, No.1, pp. 1-9, 2022. DOI: https:\/\/doi.org\/10.5687\/iscie.35.<\/a><\/li>\n
                      2. Ziang Liu and Tatsushi Nishi, Strategy Dynamics Particle Swarm Optimizer, Information Sciences, Vol. 582, pp. 665-708, 2022, DOI: https:\/\/doi.org\/10.1016\/j.ins.2021.10.02.<\/a><\/li>\n
                      3. Kazuki Nonoyama, Ziang Liu, Tomofumi Fujiwara, Md Moktadir Alam, Tatsushi Nishi, Energy-Efficient Robot Configuration and Motion Planning Using Genetic Algorithm and Particle Swarm\u00a0 Optimization, Energies, Vol. 15, No. 2074, pp. 1-20, 2022. DOI: https:\/\/doi.org\/10.3390\/en15062074<\/a><\/li>\n
                      4. Jun Nakao, Tatsushi Nishi, Ziang Liu, A Bilevel Production Planning Using Machine Learning Based Customer Modeling, Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol. 16, No. 4, JAMDSM0037, https:\/\/doi.org\/10.1299\/jamdsm.2022jamdsm0037<\/a><\/li>\n
                      5. Hidetoshi Togo, Kohei Asanuma, Tatsushi Nishi, Ziang Liu, Machine Learning and Inverse Optimization for Estimation of Weighting Factors in Multi-Objective Production Scheduling Problems, https:\/\/doi.org\/10.3390\/app12199472<\/a><\/li>\n<\/ol>\n

                        \u56fd\u969b\u4f1a\u8b70\u8ad6\u6587<\/p>\n

                          \n
                        1. Ryuichi Kamiebisu. Taiki Saso, Jun Nakao, Kohei Ouchi, Ziang Liu, Tatsushi Nishi, Michiko Matsuda, Use Cases of the Platform for Structuring a Smart Supply Chain in a Discrete Manufacturing, Proceedings of International Conference on Manufacturing Systems 2022.<\/li>\n
                        2. Hidetoshi Togo, Kohei Asanuma, Tatsushi Nishi, Machine Learning and Inverse Optimization Approach for Model Identification of Scheduling Problems in Chemical Batch Plants, Proceedings of PSE 2022, 2022.<\/li>\n
                        3. Md Moktadir Alam, Tatsushi Nishi, Inclusion of Rapidly Exploring Random Tree Based Optimal Motion Planning Algorithm for 6-DOF Industrial Robots, Proceedings of International Symposium on Flexible Automation (ISFA2022), ISFA2022-033, 2022.<\/li>\n
                        4. Kohei Ouchi, Ziang Liu, Tatsushi Nishi, Data-Driven Multi-Objective Evolutionary Optimization for Inventory Management in Complex and Large-Scale Supply Chains, Proceedings of International Symposium on Flexible Automation (ISFA2022), ISFA2022-024, 2022.<\/li>\n
                        5. Tomoya Kawabe, Tatsushi Nishi, A Flexible Collision-Free Trajectory Planning for Multiple Robot Arms by Combining Q-Learning and RRT*, Proceedings of IEEE International Conference on Automation Science and Engineering (CASE 2022), pp. 2363-2368, 2022.<\/li>\n
                        6. Junjie He, Tatsushi Nishi, An Optimization System for Motion Planning of 6-DOF Manipulators based on Process Mining of Alpha Plus algorithm using Petri Nets, SICE Annual Conference in Kumamoto 2022, ThB02.1, 2022.<\/li>\n
                        7. Naoto Debuchi, Tatsushi Nishi, Ziang Liu, Distributed Optimization for Supply Chain Planning for Multiple Companies Using Subgradient Method and Consensus Control, IFIP Advances in Information and Communication Technology, pp. 216-213, 2022.<\/li>\n
                        8. Takuma Bando, Tatsushi Nishi, Md Moktadir Alam, Ziang Liu, Tomofumi Fujiwara, Automatic Generation of Optimization Model Using Process Mining and Petri Nets for Optimal Motion Planning of 6-DOF Manipulators, Proceedings of IEEE International Conference on Intelligent Robots and Systems, pp. 11767-11772, 2022.<\/li>\n
                        9. Yushi Oyama, Tatsushi Nishi, Ziang Liu, Md Moktadir Alam, Tomofumi Fujiwara, Decision Support System for Selecting Robot Systems for Pick-and-place Operation of Robot Manipulator, Proceeding of IEEE International Conference on Industrial Engineering and Engineering Management, pp. 530-534, 2022.<\/li>\n
                        10. Yu Nishihata, Ziang Liu, Tatsushi Nishi, Epidemiological Model of COVID-19 based on Evolutionary Game Theory: Considering the Viral Mutations, Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management, pp. 686-690, 2022.<\/li>\n
                        11. Tomoya Kawabe, Ziang Liu, Tatsushi Nishi, Md Moktadir Alam, Tomofumi Fujiwara, Optimal Motion Planning and Layout Design in Robotic Cellular Manufacturing Systems, Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1541-1545, 2022.<\/li>\n<\/ol>\n

                          2021\u5e74<\/p>\n

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                            \n
                          1. Rogyayyeh Alizadeh, Tatsushi Nishi, Jafer Bagherinejad, Mahdi Bashri, Multi-Period Maximal Covering Location Problem with Capacitated Facilities and Modules for Natural Disaster Relief Services, Applied Sciences, Vol. 11, No. 1, pp. 1-22, 397, 2021. DOI: https:\/\/doi.org\/10.3390\/app11010397<\/a><\/li>\n
                          2. Guoqing Zhang, Xiaoting Shang, Fawzat Alawneh, Yiqin Yang, Tatsushi Nishi, Integrated Production Planning and Warehouse Storage Assignment Problem: IoT Assisted Case, International Journal of Production Economics, Vol. 234, 108058, 2021. DOI: https:\/\/doi.org\/10.1016\/j.ijpe.2021.108058<\/a><\/li>\n
                          3. Michiko Matsuda, Tatsushi Nishi, Ryuichi Kamiebisu, Mao Hasegawa, Roghayyeh Alizadeh, Ziang Liu, Use of Virtual Supply Chain Constructed by Cyber-Physical Systems Concept, Procedia CIRP, 351-356, 2021, DOI: https:\/\/doi.org\/10.1016\/j.procir.2021.11.059<\/a><\/li>\n<\/ol>\n

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                              \n
                            1. Kazuki Nonoyama, Tatsushi Nishi, Energy-Efficient Motion Planning for Dual-Armed Robot by PID Gain Optimization with Genetic Algorithm, Proceedings of IEEE International Conference on Automation Science and Engineering 2021, Paper WeBT7.3, 2021.<\/li>\n
                            2. Hidetoshi Togo, Kohei Asanuma, Tatsushi Nishi, Estimating Weighting Factors Using Approximate Solutions of Multi-Objective Scheduling Problems, Proceedings of International Symposium on Scheduling 2021, pp. 30-32, 2021.<\/li>\n
                            3. Jun Nakao, Tatsushi Nishi, A Bilevel Production Planning Using Machine Learning Based Customer Modeling, Proceedings of International Symposium on Scheduling 2021, pp. 5-9, 2021.<\/li>\n
                            4. Ziang Liu, Tatsushi Nishi, Adaptive Comprehensive Learning Particle Swarm Optimization with a Parameter Control Method, Proceedings of International Symposium on Scheduling 2021, pp. 66-68, 2021.<\/li>\n
                            5. Taiki Saso, Tatsushi Nishi, Coalition Analysis on Two Manufacturers and Two Retailers Supply Chain via Cooperative Game Theory, Proceedings of International Conference on Advances in Production Management Systems, 2021.<\/li>\n
                            6. Shiya Korekane and Tatsushi Nishi, Neural Network Assisted Branch-and-Bound Method for Dynamic Berth Allocation Problems, Proceedings of IEEE International Conference on Systems, Man and Cybernetics 2021, pp. 208-213, 2021.<\/li>\n<\/ol>\n

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                                \n
                              1. Okihiro Yoshida, Tatsushi Nishi, Guoqing Zhang, and Jun Wu, Design of Optimal Quantity Discounts for Multi-Period Bilevel Planning under Uncertain Demands, Advance in Mechanical Engineering, Vol. 12, No. 2, pp. 1-17, 4020902321, February 2020. DOI: https:\/\/doi.org\/10.1177\/1687814020902321.<\/a><\/li>\n
                              2. Tatsushi Nishi, Tatsuya Okura, Eduardo Lalla-Ruiz, Stefan Vo\u00df, A Dynamic Programming-Based Matheuristic for the Dynamic Berth Allocation Problem, Annals of Operations Research, Vol. 286, pp. 391-410, March 2020. DOI: https:\/\/doi.org\/10.1007\/s10479-017-2715-9<\/a><\/li>\n
                              3. Jun Wu, Hui Yang, Yuan Cheng, Tatsushi Nishi, and T.C.E. Cheng, An N-Enterprise Investment Game under Risk of Domino Accidents in a Chemical Cluster: Nash and Pareto Equilibria, Computers and Chemical Engineering, Vol. 134, No. 4, 106705, March 2020. DOI: https:\/\/doi.org\/10.1016\/j.compchemeng.2019.106705<\/a><\/li>\n
                              4. Tatsushi Nishi, Shuhei Akiyama, Toshimitsu Higashi, Kenji Kumagai, Cell-based Local Search Heuristics for Guide Path Design of Automated Guided Vehicle Systems with Dynamic Multi-Commodity Flow, IEEE Transactions on Automation Science and Engineering, Vol. 17, No. 2, pp. 966-980, June 2020. DOI: 10.1109\/TASE.2019.295292<\/a><\/li>\n
                              5. Ziang Liu, Tatsushi Nishi, Analyzing just-in-time purchasing strategy in supply chains using an evolutionary game approach, Journal of Advanced Mechanical Design, Systems and Manufacturing, Vol. 14, No. 5, 19-00657, July 2020. DOI: https:\/\/doi.org\/10.1299\/jamdsm.2020jamdsm0070<\/a><\/li>\n
                              6. Tatsushi Nishi, Michiko Matsuda, Mao Hasegawa, Roghayyeh Alizadeh, Ziang Liu, Takuto Terunuma, Automatic construction of virtual supply chain as multi-agent system using enterprise e-catalogues, International Journal of Automation Technology, Vol. 14, No. 5, pp. 713-722, September 2020. DOI: https:\/\/doi.org\/10.20965\/ijat.2020.p0713<\/a><\/li>\n
                              7. Rogyayyeh Alizadeh, Tatsushi Nishi, Hybrid Set Covering and Dynamic Modular Covering Location Problem: Application to an Emergency Humanitarian Logistics Problem, Applied Sciences, Vol. 10, No. 20, 7110, October 2020. DOI: https:\/\/doi.org\/10.3390\/app10207110<\/a><\/li>\n
                              8. Ziang Liu, Tatsushi Nishi, Multipopulation Ensemble Particle Swarm Optimizer for Engineering Design Problems, Mathematical Problems in Engineering, 1450985, October 2020. DOI: https:\/\/doi.org\/10.1155\/2020\/145098<\/a><\/li>\n<\/ol>\n

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                                  \n
                                1. Chujo Taichi, Kosei Nishida, Tatsushi Nishi, A Conflict-Free Routing Method for Automated Guided Vehicles Using Reinforcement Learning, Proceedings of 2020 International Symposium on Flexible Automation, ISFA2020-9620, 2020.<\/li>\n
                                2. Kohei Asanuma, Tatsushi Nishi, Estimation of Weights for Multi-Objective Production Scheduling Problems -An Inverse Optimization Approach-, Proceedings of IEEE IEEM 2020, 2020.<\/li>\n<\/ol>\n

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                                  <\/p>","protected":false},"excerpt":{"rendered":"

                                  2025\u5e74 \u30b8\u30e3\u30fc\u30ca\u30eb\u8ad6\u6587 Tomoya Kawabe, Tatsushi Nishi, Ziang Liu, Tomofuji Fujiwara, Surrogate-Assisted Motion Planning […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-829","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/isopt.is.ritsumei.ac.jp\/nishilab\/index.php?rest_route=\/wp\/v2\/pages\/829","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/isopt.is.ritsumei.ac.jp\/nishilab\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/isopt.is.ritsumei.ac.jp\/nishilab\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/isopt.is.ritsumei.ac.jp\/nishilab\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/isopt.is.ritsumei.ac.jp\/nishilab\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=829"}],"version-history":[{"count":44,"href":"https:\/\/isopt.is.ritsumei.ac.jp\/nishilab\/index.php?rest_route=\/wp\/v2\/pages\/829\/revisions"}],"predecessor-version":[{"id":1213,"href":"https:\/\/isopt.is.ritsumei.ac.jp\/nishilab\/index.php?rest_route=\/wp\/v2\/pages\/829\/revisions\/1213"}],"wp:attachment":[{"href":"https:\/\/isopt.is.ritsumei.ac.jp\/nishilab\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=829"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}