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                    考慮能耗節約的集裝箱碼頭雙小車岸橋與AGV聯合配置及調度優化

                    范厚明 郭振峰 岳麗君 馬夢知

                    范厚明, 郭振峰, 岳麗君, 馬夢知. 考慮能耗節約的集裝箱碼頭雙小車岸橋與AGV聯合配置及調度優化. 自動化學報, 2020, 45(1): 1?15 doi: 10.16383/j.ass.c190626
                    引用本文: 范厚明, 郭振峰, 岳麗君, 馬夢知. 考慮能耗節約的集裝箱碼頭雙小車岸橋與AGV聯合配置及調度優化. 自動化學報, 2020, 45(1): 1?15 doi: 10.16383/j.ass.c190626
                    Fan Hou-Ming, Guo Zhen-Feng, Yue Li-Jun, Ma Meng-Zhi. Joint configuration and scheduling optimization of dual-trolley quay crane and AGV for container terminal with considering energy saving. Acta Automatica Sinica, 2020, 45(1): 1?15 doi: 10.16383/j.ass.c190626
                    Citation: Fan Hou-Ming, Guo Zhen-Feng, Yue Li-Jun, Ma Meng-Zhi. Joint configuration and scheduling optimization of dual-trolley quay crane and AGV for container terminal with considering energy saving. Acta Automatica Sinica, 2020, 45(1): 1?15 doi: 10.16383/j.ass.c190626

                    考慮能耗節約的集裝箱碼頭雙小車岸橋與AGV聯合配置及調度優化

                    doi: 10.16383/j.ass.c190626
                    基金項目: 國家自然科學基金(61473053); 遼寧省重點研發計劃指導計劃(2018401002)資助
                    詳細信息
                      作者簡介:

                      范厚明:大連海事大學交通運輸工程學院教授, 博士. 主要研究方向為交通運輸系統規劃與設計, 戰略管理與系統規劃. 本文通訊作者.Email: fhm468@163.com

                      郭振峰:大連海事大學交通運輸工程學院博士研究生. 主要研究方向為交通運輸規劃與管理;Email: guozhenfeng_dl@126.com

                      岳麗君:大連海事大學交通運輸工程學院碩士研究生. 主要研究方向為物流工程.E-mail: Yuelj11@163.com

                      馬夢知:大連海事大學交通運輸工程學院講師, 博士. 主要研究方向為交通運輸系統規劃與設計, 戰略管理與系統規劃.E-mail: mengzhi1440@126.com

                    Joint Configuration and Scheduling Optimization of Dual-trolley Quay Crane and AGV for Container Terminal with Considering Energy Saving

                    Funds: National Natural Science Foundation of China (61473053), the Key Research Plan Guidance Plan of Liaoning Province (2018401002)
                    • 摘要: 合理調度集裝箱碼頭的裝卸設備以減少生產過程中的能耗, 對實現其低碳綠色化發展具有重要意義. 針對集裝箱碼頭向自動化發展過程中的雙小車岸橋與AGV聯合配置及調度問題, 考慮AGV續航時間、雙小車岸橋中轉平臺容量和堆場緩沖支架容量約束, 以岸橋的能耗最小為第一階段模型的優化目標, 以AGV運輸過程的能耗最小為第二階段目標建立兩階段優化模型; 設計枚舉法求解第一階段模型, 改進遺傳算法求解第二階段優化模型. 以洋山四期自動化集裝箱碼頭為例進行實驗分析, 針對不同船舶在港總裝卸時間和AGV配置原則進行實驗, 驗證了模型和算法的有效性, 結果表明以最小化能耗為目標的雙小車岸橋與AGV聯合調度可在岸橋主小車不延誤的前提下, 顯著減少AGV的配置數量.
                    • 圖  1  雙小車岸橋示意圖

                      Fig.  1  The dual-trolley quay crane

                      圖  2  碼頭布局和AGV運輸流程示意圖

                      Fig.  2  Automated container terminal layout and AGV transportation process

                      圖  3  待裝卸集裝箱分布示意圖

                      Fig.  3  Containers to be loaded and unloaded

                      圖  4  岸橋任務編號示意圖

                      Fig.  4  Task number of quay crane

                      圖  5  染色體示意圖

                      Fig.  5  The chromosome

                      圖  6  目標函數求解流程圖

                      Fig.  6  Solution flowchart

                      圖  7  交叉和變異

                      Fig.  7  Crossover and variation

                      圖  8  待裝卸集裝箱船

                      Fig.  8  The ship of containers to be loaded and unloaded

                      圖  9  岸橋作業路線圖

                      Fig.  9  Path to the dual-trolley quay cranes

                      圖  10  不同AGV配置數量下各實驗的AGV利用率

                      Fig.  10  AGV utilization rate of each experiment under different configurations

                      表  1  設備參數取值

                      Table  1  Equipment parameter value

                      參數取值
                      ${\tau _1}/\min $1
                      ${\tau _2}/\min $2
                      ${\tau _3}/\min $1
                      ${\tau _4}/\min $3
                      ${\tau _5}/\min $5
                      ${v_1}/[m \cdot {\min ^{ - 1}}]$210
                      ${v_0}/[m \cdot {\min ^{ - 1}}]$350
                      ${C_1}/\left[ {kw \cdot h \cdot { {\left( {h \cdot{\simfont\text{臺} } } \right)}^{ - 1} } } \right]$91.24
                      ${C_2}/[kw \cdot h \cdot {(h \cdot {\simfont\text{臺} })^{ - 1} }]$70.18
                      ${C_3}/[kw \cdot h \cdot {(h \cdot {\simfont\text{臺} })^{ - 1} }]$49.6
                      ${C_4}/[kw \cdot h \cdot {(h \cdot {\simfont\text{臺} })^{ - 1} }]$49.6
                      ${C_5}/[kw \cdot h \cdot {(h \cdot {\simfont\text{輛} })^{ - 1} }]$21
                      ${C_6}/[kw \cdot h \cdot {(h \cdot {\simfont\text{輛} })^{ - 1} }]$14
                      ${C_7}/[kw \cdot h \cdot {(h \cdot{\simfont\text{輛} })^{ - 1} }]$9
                      下載: 導出CSV

                      表  2  岸橋調度方案比較

                      Table  2  Comparison of dual-trolley quay crane scheduling schemes

                      $k$${T_{Ik}}$${F_1}$調度方案開始-完工時刻
                      24 70911 507QC1B1- B6卸船作業0?917 min
                      B1-B18裝船作業924?3 789 min
                      QC2B7-B20卸船作業0?3 787 min
                      B19-B20裝船作業3 789?3 889 min
                      32 60511 504QC1B1-B3卸船作業0?640 min
                      B1-B13裝船作業643?2 605 min
                      QC2B3-B10卸船作業0?1 740 min
                      B14-B18裝船作業1 743?2 546 min
                      QC3B11-B20卸船作業0?2 323 min
                      B19-B20裝船作業2 324?2 429 min
                      42 63611 484QC1B1-B3卸船作業0?640 min
                      B1-B9裝船作業644?1 970 min
                      QC2B4-B5卸船作業0?93 min
                      B10-B11裝船作業98?395 min
                      QC3B6-B10卸船作業0?1 646 min
                      B12-B16裝船作業1 648?2 636 min
                      QC4B11-B20卸船作業0?2 325 min
                      B17-B20裝船作業2 331?2 468 min
                      下載: 導出CSV

                      表  3  AGV調度結果

                      Table  3  The scheduling results of AGV

                      AGV集裝箱作業序列
                      11→7→11→16→22→25→36→47→54→59→63→70→78→83→86→89→96→107→113→131→···→
                      3530→3537→3545→3548→3555→3562→3567→3572→3575→3580→3585→3588
                      22→5→8→13→17→18→21→27→31→37→48→58→61→67→74→80→82→90→94→98→115→···→
                      3336→3344→3348→3354→3355→3361→3367→3377→3382→3393→3398
                      33→4→9→14→20→23→29→32→40→44→46→49→56→62→72→85→87→92→102→114→···→
                      3747→3750→3751→3753→3754→3755→3757→3758→3760→3761→3762→3766→3767
                      46→10→12→24→34→38→42→51→60→64→69→73→76→84→88→93→99→100→105→110→···→
                      3653→3655→3658→3661→3664→3665→3668→3674→3677→3680→3687→3691→3697
                      515→19→26→33→43→75→95→109→112→118→122→125→130→141→146→150→154→162→···→
                      3538→3543→3551→3565→3569→3574→3578→3584→3592→3598→3605→3610→3614
                      628→35→39→45→50→53→55→65→71→79→91→97→101→104→108→120→123→133→136→···→
                      3742→3744→3746→3748→3749→3752→3756→3759→3763→3764→3765→3768→3769
                      730→41→52→57→66→68→77→81→103→106→111→117→121→138→142→167→170→185→···→
                      3702→3703→3707→3709→3710→3712→3716→3718→3721→3727→3730→3733→3738
                      下載: 導出CSV

                      表  4  平均計算結果與下界的比較

                      Table  4  Comparison of average calculation results with lower boundary

                      實驗$N$${T_{{q_{\max }}}}$${f_1}$${A_1}$${f_2}$${A_2}$${f_2}^*$$\underline {{f_2}} $$GA{P_1}$$GA{P_2}$
                      1240187763.96197.736333.55190.133.85 %43.00 %
                      24082901 287.76339.076612.01335.980.91 %45.10 %
                      38295752 558.76706.8161 160.60671.085.05 %42.18 %
                      41 1297903 467.661 005.1161 749.47861.6514.27 %50.75 %
                      51 5051 1024 613.561 379.9462 114.891 190.3413.74 %43.72 %
                      61 9761 3916 045.962 323.1472 996.721 927.8817.01 %35.67 %
                      72 4191 6427 394.472 492.0783 634.972 191.9112.04 %39.70 %
                      82 6491 7928 091.682 789.6283 941.742 571.837.81 %34.75 %
                      下載: 導出CSV

                      表  5  不同船舶在港總裝卸時間和不同AGV配置原則下調度結果比較

                      Table  5  The results of different allowable laytime and different AGV configuration principles

                      實驗${t_f}/h$${T_{{q_{\max }}}}/h$K/臺${f_1}/kw \cdot h$$\min ({f_1} + {f_2})/kw \cdot h $AGV配置原則一AGV配置原則二AGV配置原則三
                      V/輛${f_2}/kw \cdot h$V/輛${f_2}/kw \cdot h$V/輛${f_2}/kw \cdot h$
                      94846.46311 499.115 374.673 875.564 417.494 198.1
                      104443.28311 505.315 362.373 857.064 030.494 168.6
                      114037.9411 482.715 308.1103 825.493 847.2123 977.6
                      123635.23411 483.815 136.893 653.073 659.6123 806.2
                      133232411 487.315 097.593 610.293 610.2123 879.0
                      下載: 導出CSV

                      表  6  考慮隨機因素影響的實驗設計

                      Table  6  Experimental design considering the influence of random factors

                      實驗實驗內容
                      14完全確定性系統. 在實驗10中岸橋調度方案的基礎上, ${\tau _2}$、${\tau _5}$、${v_0}$和${v_1}$均設為定值
                      15在實驗14的基礎上, 每個集裝箱的岸橋主小車作業時間設定為服從均值為${\tau _2}$的泊松分布
                      16在實驗15的基礎上, AGV往返充電站時間設定為服從均值為${\tau _5}$負指數分布的類型
                      17在實驗16的基礎上, AGV的空載速度、重載速度分別設定為服從均值為${v_0}$和${v_1}$的正態分布
                      下載: 導出CSV

                      表  7  考慮隨機因素影響的實驗結果

                      Table  7  Experimental results considering the influence of random factors

                      $A$實驗14實驗15實驗16實驗17
                      $Del$$\rho $$f'_2$$Del$$\rho $$f'_2$$Del$$\rho $$f'_2$$Del$$\rho $$f'_2$
                      7055.56 %3 857.002.3033.80 %6 393.5349.9834.87 %6 196.18128.0835.55 %6 076.48
                      8051.42 %4 171.032.5231.97 %6 766.147.8132.51 %6 629.521.0334.00 %6 355.70
                      9051.52 %4 168.56030.32 %7 125.263.0933.71 %6 407.801.8731.34 %6 897.39
                      10050.79 %4 049.60031.63 %6 817.67032.64 %6 604.884.2531.17 %6 919.12
                      11050.42 %4 122.80030.53 %7 069.71030.10 %7 164.511.2629.55 %7 325.53
                      下載: 導出CSV
                      360彩票
                    • [1] 丁進良, 楊翠娥, 陳遠東, 柴天佑. 復雜工業過程智能優化決策系統的現狀與展望. 自 動化學報, 2018, 44(11): 1931?1943

                      1 Ding Jin-Liang, Yang Cui-E, Chen Yuan-Dong, Chai Tian-You. Research progress and prospects of intelligent optimization decision making in complex industrial process. Acta Automatica Sinica, 2018, 44(11): 1931?1943
                      [2] 2 Sim J. A carbon emission evaluation model for a container terminal. Journal of Cleaner Production, 2018, 186(10): 526?533
                      [3] 鄭松, 吳曉林, 王飛躍, 林東東, 鄭蓉, 柯偉林, 池新棟, 陳德旺. 平 行系統方法在自動化集裝箱碼頭中的應用研究. 自 動化學報, 2019, 45(3): 490?504

                      3 Zheng Song, Wu Xiao-Lin, Wang Fei-Yue, Lin Dong-Dong, Zheng Rong, Ke Wei-Lin, Chi Xin-Dong, Chen De-Wang. Applying the parallel systems approach to automatic container terminal. Acta Automatica Sinica, 2019, 45(3): 490?504
                      [4] 4 He J, Huang Y, Yan W. Yard crane scheduling in a container terminal for the trade-off between efficiency and energy consumption. Advanced Engineering Informatics, 2015, 29(1): 59?75 doi: 10.1016/j.aei.2014.09.003
                      [5] Chang D, He J, Bian Z. An investigation into berth and quay crane scheduling for container terminals based on knowledge. In: Proceedings of International Conference on Future Information Technology and Management Engineering. Changzhou, China: IEEE, 2010. 63−66
                      [6] 6 H e, J. Berth allocation and quay crane assignment in a container terminal for the trade-off between time-saving and energy-saving. Advanced Engineering Informatics, 2016, 30(3): 390?405 doi: 10.1016/j.aei.2016.04.006
                      [7] 7 Chang, D, Fang T, Fan Y. Dynamic rolling strategy for multi-vessel quay crane scheduling. Advanced Engineering Informatics, 2017, 34(10): 60?69
                      [8] 8 Zhang, Z, Zhang Z, Liu M, Lee C Y, Wang J. The quay crane scheduling problem with stability constraints. IEEE Transactions on Automation Science and Engineering, 2018, 15(3): 1399?1412 doi: 10.1109/TASE.2018.2795254
                      [9] 9 Liu D, Ge Y E. Modeling assignment of quay cranes using queueing theory for minimizing CO2 emission at a container terminal. Transportation Research Part D: Transport and Environment, 2018, 61(6): 140?151
                      [10] 10 Liang C, Fan L, Xu D, Ding Y, Gen M. Research on coupling scheduling of quay crane dispatch and configuration in the container terminal. Computers & Industrial Engineering, 2018, 125(11): 649?657
                      [11] 11 Msakni M K, Diabat A, Rabadi G, Salem M A, Kotachi M. Exact methods for the quay crane scheduling problem when tasks are modeled at the single container level. Computers & Operations Research, 2018, 99(11): 218?233
                      [12] 12 Kim K H, Park Y M. A crane scheduling method for port container terminals. European Journal of Operational Research, 2004, 156(3): 752?768 doi: 10.1016/S0377-2217(03)00133-4
                      [13] 13 Nguyen S, Zhang M, Johnston M, Tan K C. Hybrid evolutionary computation methods for quay crane scheduling problems. Computers & Operations Research, 2013, 40(8): 2083?2093
                      [14] 14 Kim K H, Bae J W. A look-ahead dispatching method for automated guided vehicles in automated port container terminals. Transportation Science, 2004, 38(2): 224?234 doi: 10.1287/trsc.1030.0082
                      [15] 15 Choe R, Kim J, Ryu K R. Online preference learning for adaptive dispatching of AGVs in an automated container terminal. Applied Soft Computing, 2016, 38(1): 647?660
                      [16] Kim J, Choe R, Ryu K R. Multi-objective optimization of dispatching strategies for situation-adaptive AGV operation in an automated container terminal. In: Proceedings of Research in Adaptive and Convergent Systems. New York, USA: ACM, 2013. 1−6
                      [17] 17 Xin J, Negenborn R R, Lodewijks G. Energy-aware control for automated container terminals using integrated flow shop scheduling and optimal control. Transportation Research Part C: Emerging Technologies, 2014, 44(7): 214?230
                      [18] 18 Peng Y, Wang W, Liu K, Li X, Tian Q. The Impact of the allocation of facilities on reducing carbon emissions from a green container terminal perspective. Sustainability, 2018, 10(6): 1813 doi: 10.3390/su10061813
                      [19] 19 Yang Y, Zhu X, Haghani A. Multiple equipment integrated scheduling and storage space allocation in rail–water intermodal container terminals considering energy efficiency. Transportation Research Record, 2019, 2673(3): 199?209 doi: 10.1177/0361198118825474
                      [20] Dkhil H, Yassine A, Chabchoub H. Optimization of container handling systems in automated maritime terminal. Advanced Methods for Computational Collective Intelligence. Berlin Heidelberg: Springer, 2013. 301−312
                      [21] 21 Yang Y, Zhong M, Dessouky Y, Postolache O. An integrated scheduling method for AGV routing in automated container terminals. Computers & Industrial Engineering, 2018, 126(12): 482?493
                      [22] 22 Singgih I K, Hong S, Kim K H. Flow path design for automated transport systems in container terminals considering traffic congestion. Industrial Engineering & Management Systems, 2016, 15(1): 19?31
                      [23] 23 Legato P, Mazza R M, Trunfio R. Simulation-based optimization for discharge/loading operations at a maritime container terminal. OR Spectrum, 2010, 32(3): 543?567 doi: 10.1007/s00291-010-0207-2
                      [24] 24 X in, J, Negenborn R R, Corman F, Lodewijks, G. Control of interacting machines in automated container terminals using a sequential planning approach for collision avoidance. Transportation Research Part C: Emerging Technologies, 2015, 60(11): 377?396
                      [25] 原豪男, 郭戈. 交通信息物理系統中的車輛協同運行優化調度. 自動化學報, 2019, 45(1): 143?152

                      25 Yuan Hao-Nan, Guo Ge. Vehicle cooperative optimization scheduling in transportation cyber physical systems. Acta Automatica Sinica, 2019, 45(1): 143?152
                      [26] 26 Lee D H, Wang H Q, Miao L. Quay crane scheduling with non-interference constraints in port container terminals. Transportation Research Part E: Logistics and Transportation Review, 2008, 44(1): 124?135 doi: 10.1016/j.tre.2006.08.001
                      [27] 羅勛杰. 全 自動化集裝箱碼頭水平運輸方式對比. 水 運工程, 2016, 42(9): 76?82

                      27 Luo Xun-Jie. Comparison of horizon transportation system of full automatic container terminal. Port &Waterway Engineering, 2016, 42(9): 76?82
                      [28] 陳超, 張哲, 曾慶成. 集裝箱碼頭混合交叉作業集成調度模型. 交 通運輸工程學報, 2012, 12(03): 92?100

                      28 Chen Chao, Zhang Zhe, Zeng Qing-Cheng. Integrated scheduling model of mixed cross-operation for container terminal. Journal of Traffic and Transportation Engineering, 2012, 12(03): 92?100
                      [29] 邢曦文, 毛鈞, 張睿, 靳志宏. 基于混合流水作業組織的集裝箱碼頭裝卸作業集成調度優化. 中 國管理科學, 2014, 22(10): 97?105

                      29 Xin Xi-Wen, Mao Jun, Zhang Rui, Jin Zhi-Hong. Optimization of container loading/unloading integrated scheduling in a container terminal based on hybrid flowshop. Chinese Journal Of Management Science, 2014, 22(10): 97?105
                      [30] 韓曉龍, 樊加偉. 自動化港口AGV調度配置仿真分析. 重慶交通大學學報(自然科學版), 2016, 35(5): 151?154+164

                      30 Han Xiao-Long, Fan Jia-Wei. Analysis of AGV dispatching and configuration simulation of automated container terminals. Journal Of Chongqing Jiaotong University (Natural Science), 2016, 35(5): 151?154+164
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                    • 收稿日期:  2019-09-03
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