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              面向可持續生產中多任務調度的雙重增強模因算法

              盧弘 王耀南 喬非 方遒

              盧弘, 王耀南, 喬非, 方遒. 面向可持續生產中多任務調度的雙重增強模因算法. 自動化學報, 2024, 50(4): 731?744 doi: 10.16383/j.aas.c230446
              引用本文: 盧弘, 王耀南, 喬非, 方遒. 面向可持續生產中多任務調度的雙重增強模因算法. 自動化學報, 2024, 50(4): 731?744 doi: 10.16383/j.aas.c230446
              Lu Hong, Wang Yao-Nan, Qiao Fei, Fang Qiu. Dual-enhanced memetic algorithm for multi-task scheduling in sustainable production. Acta Automatica Sinica, 2024, 50(4): 731?744 doi: 10.16383/j.aas.c230446
              Citation: Lu Hong, Wang Yao-Nan, Qiao Fei, Fang Qiu. Dual-enhanced memetic algorithm for multi-task scheduling in sustainable production. Acta Automatica Sinica, 2024, 50(4): 731?744 doi: 10.16383/j.aas.c230446

              面向可持續生產中多任務調度的雙重增強模因算法

              doi: 10.16383/j.aas.c230446
              基金項目: 湖南創新型省份建設科技重大專項 (2021GK1010), 國家自然科學基金 (62293510), 湖南省自然科學基金 (2023JJ30162), 岳麓山工業創新中心重大項目 (2023YCII0102), 湖南省教育廳科學研究項目優秀青年項目 (23B0029) 資助
              詳細信息
                作者簡介:

                盧弘:湖南大學電氣與信息工程學院博士后. 2022 年獲得同濟大學博士學位. 主要研究方向為生產調度與智能優化. E-mail: luhong@hnu.edu.cn

                王耀南:中國工程院院士, 湖南大學電氣與信息工程學院教授. 1995 年獲得湖南大學博士學位. 主要研究方向為機器人學, 智能控制和圖像處理. E-mail: yaonan@hnu.edu.cn

                喬非:同濟大學電子與信息工程學院教授. 1997 年獲得同濟大學博士學位. 主要研究方向為復雜制造計劃與調度, 智能生產系統以及能源管理與優化. E-mail: fqiao@#edu.cn

                方遒:湖南大學電氣與信息工程學院副教授. 2017 年獲得同濟大學博士學位. 主要研究方向為復雜工業過程建模與優化. 本文通信作者. E-mail: qfang@hnu.edu.cn

              Dual-enhanced Memetic Algorithm for Multi-task Scheduling in Sustainable Production

              Funds: Supported by Special Funding Support for the Construction of Innovative Provinces in Hunan Province (2021GK1010), National Natural Science Foundation of China (62293510), Hunan Provincial Natural Science Foundation (2023JJ30162), Major Project of Yuelushan Industrial Innovation Center (2023YCII0102), and Hunan Provincial Department of Education Scientific Research Project (23B0029)
              More Information
                Author Bio:

                LU Hong Postdoctor at the College of Electrical and Information Engineering, Hunan University. He received his Ph.D. degree from Tongji University in 2022. His research interest covers production scheduling and intelligent optimization

                WANG Yao-Nan Academician at Chinese Academy of Engineering, professor at the College of Electrical and Information Engineering, Hunan University. He received his Ph.D. degree from Hunan University in 1995. His research interest covers robotics, intelligent control, and image processing

                QIAO Fei Professor at the College of Electronics and Information Engineering, Tongji University. She received her Ph.D. degree from Tongji University in 1997. Her research interest covers complex manufacturing planning and scheduling, intelligent production systems, and energy management and optimization

                FANG Qiu Associate professor at the College of Electrical and Information Engineering, Hunan University. He received his Ph.D. degree from Tongji University in 2017. His research interest covers modeling and optimization of complex industrial processes. Corresponding author of this paper

              • 摘要: 從經濟、環境和社會3個維度, 全面提升生產調度方案的可持續性具有重要意義. 針對并行機生產場景, 建立考慮機器指派、加工順序、人員安排以及開關機控制等4種決策任務的調度模型. 為實現對復雜決策空間的高效尋優, 提出一種融合兩種局部優化策略的雙重增強模因算法(Dual-enhanced memetic algorithm, DMA)求解模型. 從隨機更新角度, 針對不同決策任務, 構造單步變鄰域搜索(One-step variable neighborhood search, 1S-VNS)策略. 從定向優化角度, 分析目標和關鍵任務之間的匹配關系, 提出一種可持續目標導向策略(Sustainable goals-oriented strategy, SGS). 考慮到兩種優化策略的不同特點, 單步變鄰域搜索策略作用于整個種群, 目標導向策略強化種群中的精英個體, 實現對輸出解集的雙重優化. 仿真實驗結果表明, 雙重優化策略能有效地增強算法性能, 并且所提算法在非支配解的多樣性和收斂性上具有優越性.
              • 圖  1  任務對應的個體編碼說明圖

                Fig.  1  An example graph of individual coding corresponding for tasks

                圖  2  社會維度目標導向的優化策略作用效果說明圖

                Fig.  2  Explanation of the effectiveness of optimization strategy guided by social dimension goal

                圖  3  經濟維度目標導向的優化策略作用效果說明圖

                Fig.  3  Explanation of the effectiveness of optimization strategy guided by economic dimension goal

                圖  4  MMA與MOA、MMA_1、MMA_2、MMA_3性能指標的均值和95%置信區間

                Fig.  4  Mean and 95% confidence interval of performance indicators of MMA, MOA, MMA_1, MMA_2 and MMA_3

                圖  5  DMA與MMA、MMA&SGS性能指標的均值和95%置信區間

                Fig.  5  Mean and 95% confidence interval of performance indicators of DMA, MAA and MMA&SGS

                圖  6  DMA與V-NSGA-II、IABC、MA性能指標的均值和95%置信區間

                Fig.  6  Mean and 95% confidence interval of performance indicators of DMA, V-NSGA-II, IABC and MA

                圖  7  DMA與V-NSGA-II、IABC、MA獲得的Pareto前沿

                Fig.  7  Pareto frontiers obtained by DMA, V-NSGA-II, IABC and MA

                表  1  MMA與MOA、MMA_1、MMA_2、MMA_3的性能指標結果

                Table  1  Results for MMA, MOA, MMA_1, MMA_2 and MMA_3

                案例 $ IGD$ $R_{{\mathrm{nd}}} $
                MOA MMA_1 MMA_2 MMA_3 MMA MOA MMA_1 MMA_2 MMA_3 MMA
                7&4&2 0.79 0.66 0.63 0.39 0.24 0.10 0.39 0.55 0.70 0.87
                7&5&3 0.79 0.65 0.58 0.86 0.33 0.13 0.39 0.47 0.42 0.72
                8&4&2 0.97 0.53 0.52 0.50 0.36 0.00 0.41 0.43 0.46 0.71
                8&5&3 0.74 0.63 0.53 0.57 0.47 0.00 0.14 0.40 0.35 0.61
                9&4&2 0.87 0.71 0.69 0.63 0.39 0.13 0.08 0.19 0.31 0.71
                9&5&3 0.64 0.57 0.63 0.59 0.35 0.00 0.19 0.11 0.32 0.75
                10&4&2 0.97 0.69 0.66 0.78 0.41 0.00 0.13 0.33 0.23 0.70
                10&5&3 0.70 0.67 0.55 0.59 0.44 0.00 0.07 0.38 0.29 0.67
                20&10&6 0.69 0.64 0.67 0.69 0.43 0.07 0.23 0.14 0.09 0.66
                20&10&8 0.67 0.82 0.80 0.73 0.36 0.15 0.02 0.11 0.13 0.70
                20&12&8 0.68 0.77 0.47 0.75 0.49 0.50 0.10 0.63 0.23 0.62
                20&12&10 0.48 0.90 0.53 0.72 0.40 0.68 0.08 0.58 0.12 0.68
                40&10&6 0.85 0.94 0.64 0.90 0.32 0.10 0.00 0.29 0.00 0.71
                40&10&8 0.92 0.91 0.62 0.65 0.31 0.05 0.08 0.28 0.12 0.78
                40&12&8 0.86 0.69 0.74 0.85 0.39 0.09 0.17 0.11 0.10 0.69
                40&12&10 0.77 0.78 0.71 0.81 0.43 0.14 0.13 0.17 0.12 0.67
                下載: 導出CSV

                表  2  DMA與MMA、MMA&SGS的性能指標結果

                Table  2  Results for DMA, MMA and MMA&SGS

                案例 $ IGD$ $R_{{\mathrm{nd}}} $
                MMA MMA&SGS DMA MMA MMA&SGS DMA
                7&4&2 0.00 0.00 0.00 1.00 1.00 1.00
                7&5&3 0.35 0.49 0.38 0.87 0.70 0.86
                8&4&2 0.45 0.51 0.39 0.71 0.48 0.76
                8&5&3 0.29 0.44 0.34 0.74 0.49 0.72
                9&4&2 0.61 0.57 0.41 0.62 0.52 0.73
                9&5&3 0.52 0.80 0.39 0.65 0.36 0.77
                10&4&2 0.80 0.80 0.36 0.47 0.46 0.77
                10&5&3 0.57 0.85 0.43 0.42 0.30 0.71
                20&10&6 0.71 0.57 0.41 0.20 0.69 0.74
                20&10&8 0.65 0.51 0.43 0.12 0.70 0.73
                20&12&8 0.71 0.44 0.47 0.22 0.74 0.72
                20&12&10 0.85 0.39 0.42 0.22 0.79 0.75
                40&10&6 0.80 0.59 0.39 0.11 0.28 0.79
                40&10&8 0.71 0.58 0.37 0.16 0.33 0.72
                40&12&8 0.73 0.83 0.42 0.19 0.30 0.71
                40&12&10 0.74 0.65 0.40 0.22 0.26 0.73
                下載: 導出CSV

                表  3  DMA與V-NSGA-II、IABC、MA的性能指標結果

                Table  3  Results for DMA, V-NSGA-II, IABC and MA

                案例 $IGD$ $R_{{\mathrm{nd}}}$
                V-NSGA-II IABC MA DMA V-NSGA-II IABC MA DMA
                7&4&2 0.85 0.67 0.48 0.15 0.00 0.15 0.70 0.87
                7&5&3 0.74 0.85 0.66 0.24 0.00 0.08 0.22 0.82
                8&4&2 0.65 0.76 0.41 0.32 0.20 0.08 0.43 0.76
                8&5&3 0.78 0.80 0.32 0.25 0.32 0.24 0.44 0.87
                9&4&2 0.41 0.63 0.56 0.36 0.39 0.34 0.37 0.76
                9&5&3 0.86 0.61 0.57 0.13 0.15 0.20 0.35 0.86
                10&4&2 0.52 0.31 0.49 0.22 0.21 0.31 0.27 0.77
                10&5&3 0.63 0.56 0.52 0.20 0.12 0.22 0.45 0.78
                20&10&6 0.85 0.88 0.69 0.21 0.07 0.05 0.15 0.83
                20&10&8 0.83 0.91 0.72 0.18 0.02 0.00 0.11 0.86
                20&12&8 0.79 0.84 0.74 0.31 0.05 0.00 0.23 0.71
                20&12&10 0.82 0.93 0.69 0.30 0.03 0.00 0.35 0.74
                40&10&6 0.78 0.81 0.55 0.11 0.00 0.00 0.15 0.85
                40&10&8 0.62 0.89 0.61 0.29 0.14 0.00 0.14 0.73
                40&12&8 0.59 0.87 0.53 0.23 0.11 0.00 0.15 0.77
                40&12&10 0.62 0.83 0.50 0.31 0.09 0.00 0.18 0.71
                下載: 導出CSV

                A1  各個工件的基本加工數據

                A1  Basic machining data for each job

                工件 機器 工人 加工時間$t$ 加工單位能耗$p^{\rm{prc}}$
                $J1$ $M1$ $W1$ 3 8
                $J1$ $M1$ $W2$ 6 6
                $J1$ $M2$ $W1$ 4 6
                $J1$ $M2$ $W2$ 2 4
                $J1$ $M3$ $W1$ 6 5
                $J1$ $M3$ $W2$ 6 6
                $J2$ $M1$ $W1$ 4 7
                $J2$ $M1$ $W2$ 2 5
                $J2$ $M2$ $W1$ 3 5
                $J2$ $M2$ $W2$ 4 8
                $J2$ $M3$ $W1$ 4 3
                $J2$ $M3$ $W2$ 3 8
                $J3$ $M1$ $W1$ 5 8
                $J3$ $M1$ $W2$ 5 7
                $J3$ $M2$ $W1$ 3 3
                $J3$ $M2$ $W2$ 2 4
                $J3$ $M3$ $W1$ 3 5
                $J3$ $M3$ $W2$ 3 7
                $J4$ $M1$ $W1$ 4 3
                $J4$ $M1$ $W2$ 4 7
                $J4$ $M2$ $W1$ 2 3
                $J4$ $M2$ $W2$ 3 6
                $J4$ $M3$ $W1$ 6 5
                $J4$ $M3$ $W2$ 2 7
                $J5$ $M1$ $W1$ 6 7
                $J5$ $M1$ $W2$ 5 8
                $J5$ $M2$ $W1$ 4 8
                $J5$ $M2$ $W2$ 4 5
                $J5$ $M3$ $W1$ 3 7
                $J5$ $M3$ $W2$ 4 4
                下載: 導出CSV

                A2  機器單位空閑能耗以及開關機能耗

                A2  Unit idle energy consumption and on/off energy consumption of machines

                機器 空閑單位能耗$p^{\rm{idle}}$ 開關機時間$t_{\rm{on/off}}$ 開關機能耗$H_{\rm{turn}}$
                $M1$ 1 2 2
                $M2$ 3 3 9
                $M3$ 3 3 6
                下載: 導出CSV
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                        出版歷程
                        • 收稿日期:  2023-07-20
                        • 錄用日期:  2024-01-23
                        • 網絡出版日期:  2024-03-29
                        • 刊出日期:  2024-04-26

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