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    题名: 陸軍軍團指揮部工兵組督導排班最佳化研究;The Optimal Scheduling Study of the Engineer Unit Supervisory Shifts at the Army Corps Command Headquarters
    作者: 賴雨婕;Lai, Yu-Jay
    贡献者: 土木工程學系在職專班
    关键词: 陸軍;督導;最佳化指派;數學規劃;Arm;supervision;optimized arrangement;mathematics programming;LINGO
    日期: 2024-01-11
    上传时间: 2024-09-19 14:12:33 (UTC+8)
    出版者: 國立中央大學
    摘要: 「陸軍司令部」每年都會修頒各項作業規定之業務檢查重點及督導檢查表,透過定期督導的方式檢驗各單位執行成效,希望能夠及時發現並解決問題,加強推動國軍政策命令。陸軍某軍團指揮部工兵組由參謀官依組內各項督導次數進行排班作業,雖可滿足每季督導次數,惟未將督導所產生之勞役度納入考量,顯有其不足之處。因此,若可將督導排班限制建構數學模式,以得最佳化排班結果,可使各項督導在更公平且有品質的狀況下完成。
    本研究以陸軍某軍團指揮部工兵組少校階以上及上尉階以下幹部為樣本,計算出基於合理勞役度的最佳化排班結果。利用數學規劃方法和LINGO,成功建構了最佳化指派模型並進行分析。透過LINGO產生的Excel文件可以提供使用者關鍵參數作為參考,包括人員數量、品質管理證書數量、監督間隔時間和監督次數變化等。;The Army Headquarters issues annual business inspection and supervision checklists to address various operational requirements. The primary objective of promoting national military policies is to proactively identify and resolve potential issues. Consequently, routine supervision and guidance are crucial to validate the effective implementation of tasks by subordinates. In the engineering group of the Army Corps Headquarters, the supervision schedule is organized by staff officers based on the appropriate supervision number for different types. However, the current arrangement lacks consideration for the labor intensity of supervision. The development of a theoretical model that considers various critical parameters is essential to optimize scheduling outcomes.
    This research focuses on the engineering group of the Army Headquarters, specifically individuals ranging from major to captain, as a sample. The goal is to calculate the optimized arrangement result based on reasonable labor intensity. Using mathematics programming methods and LINGO, we successfully construct an optimized scheduling model for analysis. Furthermore, the output generated by LINGO provides critical parameters as a reference for users, including the number of personnel, the quantity of quality control certificates, intervals between supervisions, and variations in the number of supervisions, among others.
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