{"id":341,"date":"2020-09-26T14:06:18","date_gmt":"2020-09-26T05:06:18","guid":{"rendered":"http:\/\/forest.sys.okayama-u.ac.jp\/nishilab\/?page_id=341"},"modified":"2025-06-13T14:28:49","modified_gmt":"2025-06-13T05:28:49","slug":"341-2","status":"publish","type":"page","link":"https:\/\/isopt.is.ritsumei.ac.jp\/nishilab\/?page_id=341","title":{"rendered":"\u7814\u7a76\u5ba4\u306e\u4fee\u58eb\u8ad6\u6587\u7d39\u4ecb"},"content":{"rendered":"

\u5e73\u621022\u5e74\u5ea6\u4fee\u58eb\u8ad6\u6587<\/span><\/a><\/p>\n

\u897f\u3001\u5289\u30b0\u30eb\u30fc\u30d7\u306e\u4fee\u58eb\u8ad6\u6587\u7d39\u4ecb<\/h2>\n
\n

2020\u5e74\u5ea6\u4fee\u58eb\u8ad6\u6587<\/span><\/a><\/p>\n

2021\u5e74\u5ea6\u4fee\u58eb\u8ad6\u6587<\/span><\/a><\/p>\n

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2022\u5e74\u5ea6\u4fee\u58eb\u8ad6\u6587<\/span><\/p>\n

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\u30fbRobust Optimization for Bilevel Production Planning under Uncertainty in Customer's Purchasing Decisions<\/p>\n

\u30fbNeural Network Assisted Search for Dynamic Berth Allocation Problem - Exact and Heuristic Procedures -<\/p>\n

\u30fbFeature Selection for Estimating Weighting Factors of Objective Functions Using Historical Data for Multi-Objective Scheduling Problems<\/p>\n

\u30fb\u30ed\u30dc\u30c3\u30c8\u30a2\u30fc\u30e0\u306b\u3088\u308b\u54c1\u51fa\u3057\u4f5c\u696d\u306b\u304a\u3051\u308b\u7d4c\u7531\u70b9\u3092\u7528\u3044\u305f\u52d5\u4f5c\u8a08\u753b\u306e\u751f\u6210\u6cd5<\/p>\n

2023\u5e74\u5ea6\u4fee\u58eb\u8ad6\u6587<\/p>\n

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\u30fbDistributed Optimization Algorithm for Unit Commitment Problem Using Lagrangian Decomposition and Coordination with Consensus Control
\u30fbSimultaneous Optimization of Equipment Selection and Placement Planning for Pick and Place Operations of Robot Manipulator
\u30fbData-Driven Optimization Approach for Task and Motion Planning of Robot Manipulators Using Symbolic Sequence Input
\u30fbEvolutionary-Game-Theory-Based Epidemiological Model for Prediction of Infections with Application to Pharmaceutical Inventory Management Problems<\/p>\n

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2024\u5e74\u5ea6\u4fee\u58eb\u8ad6\u6587<\/p>\n

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\u30fbDeep Q-Network\u3092\u7528\u3044\u305f\u8907\u6570\u53f0\u79fb\u52d5\u30ed\u30dc\u30c3\u30c8\u306e\u30bf\u30b9\u30af\u5272\u5f53\u3068\u7d4c\u8def\u8a08\u753b\u6cd5<\/p>\n

\u30fbDeep Reinforcement Learning for Dynamic Pricing and Ordering Policies in Perishable Inventory Management<\/p>\n\n\n

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

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