本文選題：調(diào)度 + 連續(xù)批　； 參考：《合肥工業(yè)大學(xué)》2014年博士論文

【摘要】：隨著網(wǎng)絡(luò)技術(shù)和全球經(jīng)濟(jì)一體化的不斷發(fā)展,供應(yīng)鏈之間的競爭越來越激烈。更多的供應(yīng)鏈成員意識(shí)到需要通過加強(qiáng)與其他成員之間的合作來提高供應(yīng)鏈的競爭力,從而能夠降低各自的生產(chǎn)運(yùn)營成本。物聯(lián)網(wǎng)技術(shù)的發(fā)展正好為供應(yīng)鏈成員之間的合作提供了信息基礎(chǔ),它不僅能夠?qū)⑸a(chǎn)和運(yùn)輸信息實(shí)時(shí)反饋到各自成員的管理中心,而且能夠及時(shí)將這些信息分享給其他合作成員。物聯(lián)網(wǎng)技術(shù)將供應(yīng)鏈成員之間的合作推進(jìn)到一個(gè)新的層面,利用好這些信息能夠低生產(chǎn)成本、增加利潤和提高客戶滿意度,從而增強(qiáng)整體供應(yīng)鏈競爭力,同時(shí)能夠進(jìn)一步拓寬了生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題的理論研究領(lǐng)域。因此,如何將該信息價(jià)值轉(zhuǎn)化為經(jīng)濟(jì)和社會(huì)效益,運(yùn)用物聯(lián)網(wǎng)信息獲得高效的生產(chǎn)運(yùn)輸協(xié)同方案成為關(guān)鍵性問題。本文以鋁制品制造供應(yīng)鏈為背景,從調(diào)度角度出發(fā)研究了物聯(lián)網(wǎng)環(huán)境下供應(yīng)鏈成員之間的生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題。 本文圍繞擠壓廠的連續(xù)批處理機(jī)加工過程,系統(tǒng)性分析了多種情形下的多階段生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題。分別考慮了運(yùn)載車輛有限情形、工件動(dòng)態(tài)到達(dá)情形、工件加工時(shí)間惡化情形、機(jī)器發(fā)生故障情形以及分布在不同地理位置的多制造商情形的協(xié)同調(diào)度問題。由于這些問題均為NP難,本文致力于分析最優(yōu)調(diào)度方案的性質(zhì),并基于這些性質(zhì)設(shè)計(jì)高效的啟發(fā)式和智能算法。另一方面,本文為這些問題推導(dǎo)了問題下界,這些下界可以用于評(píng)價(jià)算法的精確度。本文對(duì)基于連續(xù)批的生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題的研究成果概括如下： (1)研究了運(yùn)載車輛有限情形下的生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題,調(diào)度目標(biāo)為最小化制造跨度時(shí)間�；谶\(yùn)載車輛有限等約束條件,建立了數(shù)學(xué)模型。根據(jù)批次在供應(yīng)商和制造商之間的運(yùn)輸時(shí)間和工件在制造商機(jī)器上加工時(shí)間的關(guān)系,將問題劃分為兩種情形。針對(duì)兩種情形,分別設(shè)計(jì)了兩種啟發(fā)式算法及問題下界�；趩栴}下界推導(dǎo)出該啟發(fā)式算法最壞情形性能比例�？紤]工件數(shù)量規(guī)模,分別設(shè)計(jì)了大量的小規(guī)模和大規(guī)模隨機(jī)數(shù)據(jù)實(shí)驗(yàn)。仿真實(shí)驗(yàn)結(jié)果表明,當(dāng)工件數(shù)量為1000時(shí),所構(gòu)造的兩種啟發(fā)式算法的平均相對(duì)差距分別收斂到0.48%和0.80%,均明顯優(yōu)于現(xiàn)有FOE and SPT算法和LOE and LPT算法。 (2)研究了工件動(dòng)態(tài)到達(dá)情形下的生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題,調(diào)度目標(biāo)為最小化制造跨度時(shí)間。基于工件動(dòng)態(tài)到達(dá)等約束條件,建立了數(shù)學(xué)模型。分析了最優(yōu)調(diào)度方案中關(guān)于工件動(dòng)態(tài)到達(dá)時(shí)間的相關(guān)性質(zhì),討論了工件同時(shí)到達(dá)特殊情形最優(yōu)調(diào)度方案和批次數(shù)量之間的關(guān)系�；谝陨蠁栴}性質(zhì),構(gòu)造了兩階段TP-H啟發(fā)式算法,并證明TP-H算法最壞情形性能比例為7/2。分別通過松弛工件到達(dá)時(shí)間和假設(shè)制造商機(jī)器上沒有額外空閑時(shí)間得出兩個(gè)問題下界�；诓煌臋C(jī)器能力設(shè)計(jì)了仿真實(shí)驗(yàn),大量仿真實(shí)驗(yàn)結(jié)果驗(yàn)證了TP-H算法的有效性。當(dāng)工件數(shù)量為1000時(shí),.所構(gòu)造的TP-H算法的平均相對(duì)差距收斂到0.21%,優(yōu)于現(xiàn)有MBF算法和MEF算法。 (3)研究了工件加工時(shí)間惡化的生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題。分析了工件加工惡化情形下的幾類單機(jī)調(diào)度問題,目標(biāo)函數(shù)分別為最小化制造跨度時(shí)間、最小化延遲工件數(shù)量、最小化工件總完工時(shí)間,設(shè)計(jì)了相應(yīng)的最優(yōu)化算法。基于單機(jī)調(diào)度問題,考慮了有緩存區(qū)情形下的生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題,建立了相應(yīng)的數(shù)學(xué)模型,目標(biāo)函數(shù)為最小化制造跨度時(shí)間。分析了最優(yōu)調(diào)度方案中組批及批次排序性質(zhì),構(gòu)建了一種最優(yōu)化算法。另外研究了無緩存區(qū)情形下的生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題,建立了基于無緩存區(qū)約束的數(shù)學(xué)模型,目標(biāo)函數(shù)為最小化制造跨度時(shí)間。分析了最優(yōu)解性質(zhì),推導(dǎo)出新的問題下界,構(gòu)建了一種啟發(fā)式算法。仿真實(shí)驗(yàn)結(jié)果表明當(dāng)工件數(shù)量大于260時(shí),該啟發(fā)式算法的平均和最大相對(duì)差距比例均小于0.01%。 (4)研究了考慮機(jī)器故障的生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題�；趦蓚�(gè)平行制造商機(jī)器可能發(fā)生故障的情形建立了數(shù)學(xué)模型,目標(biāo)函數(shù)為最小化制造跨度時(shí)間。分析了最優(yōu)調(diào)度方案性質(zhì),推導(dǎo)出問題下界。分別構(gòu)建了兩種情形下的調(diào)度規(guī)則,基于這些調(diào)度規(guī)則,設(shè)計(jì)了新的啟發(fā)式算法。大量的仿真實(shí)驗(yàn)結(jié)果說明了該啟發(fā)式算法能夠高效地解決不同規(guī)模的問題。 (5)研究了分布在不同地理位置多制造商的生產(chǎn)運(yùn)輸協(xié)同調(diào)度問題,基于不同地理位置的多制造商等特點(diǎn)建立了相應(yīng)的數(shù)學(xué)模型,目標(biāo)函數(shù)為最小化整個(gè)制造過程的跨度時(shí)間。分析了該問題的最優(yōu)解性質(zhì)。提出了新穎的MGSA算法,設(shè)計(jì)了編碼修正策略、初始化種群方法和最優(yōu)種群保存策略,提出了插入操作、互換操作和變異操作。針對(duì)工件組批問題,構(gòu)建了動(dòng)態(tài)規(guī)劃與啟發(fā)式規(guī)則結(jié)合的DP-H混合算法。大量的仿真實(shí)驗(yàn)結(jié)果表明MGSA算法優(yōu)于現(xiàn)有的GA和PSO算法。
[Abstract]:With the continuous development of network technology and global economic integration, the competition between supply chains is becoming more and more intense. More members of the supply chain are aware of the need to improve the competitiveness of the supply chain by strengthening the cooperation with other members, thus reducing the cost of their respective production and operation. The development of the Internet of things is just a supply chain. The cooperation between members provides the information base. It can not only feed the production and transportation information back to the management center of their own members in real time, but also share the information to other cooperative members in time. The technology of the Internet of things will push the cooperation among the members of the supply chain to a new level, and the use of these information can be used as a low production. Cost, increase profit and improve customer satisfaction, thus enhance the competitiveness of the overall supply chain, and further broaden the theoretical research field of production and transportation cooperation scheduling problem. Therefore, how to convert the value of the information into economic and social benefits, and to use the information and interest of the Internet of things to obtain efficient production and transportation cooperation scheme is the key to the problem. In this paper, based on the supply chain of aluminum products manufacturing, this paper studies the cooperative scheduling problem between the members of the supply chain in the environment of the Internet of things from the perspective of scheduling.
In this paper, the cooperative scheduling problem of multistage production and transportation in a variety of cases is systematically analyzed in the process of continuous batch processing in the extrusion plant. The finite situation of vehicles, the dynamic arrival of the workpiece, the deterioration of the working time of the workpiece, the failure of the machine and the multi manufacturer distributed in different geographical locations are considered respectively. Because these problems are all NP difficult, this paper focuses on the analysis of the properties of optimal scheduling schemes, and designs efficient heuristic and intelligent algorithms based on these properties. On the other hand, this paper derives the lower bounds for these problems. These lower bounds can be used to evaluate the accuracy of the algorithm. The research results of production and Transportation Co scheduling are summarized as follows:
(1) the cooperative scheduling problem of production and transportation under the limited condition of carrying vehicles is studied. The scheduling goal is to minimize the span of manufacturing span. A mathematical model is set up based on the limited conditions such as the limited transport vehicle. The problem is based on the relationship between the time of the batch and the processing time between the manufacturer and the manufacturer on the manufacturer's machine. It is divided into two cases. For two cases, two heuristic algorithms and the lower bounds are designed respectively. Based on the lower bounds of the problem, the worst case performance ratio of the heuristic algorithm is derived. A large number of small scale and large-scale random data experiments are designed considering the size of the workpiece. The simulation experiment results show that when the number of workpieces is 1000 The average relative difference between the two heuristic algorithms is 0.48% and 0.80% respectively, which are significantly better than the existing FOE and SPT algorithm and LOE and LPT algorithm.
(2) the cooperative scheduling problem of production and transportation is studied under the dynamic arrival of the workpiece. The scheduling goal is to minimize the span of manufacturing span. A mathematical model is established based on the constraint conditions of the dynamic arrival of the workpiece. The related properties of the dynamic arrival time of the workpiece in the optimal scheduling scheme are analyzed, and the optimal situation is discussed at the same time. The relationship between scheduling and batch number. Based on the properties of the above problems, a two stage TP-H heuristic algorithm is constructed, and the worst case performance ratio of the TP-H algorithm is 7/2., respectively, by relaxing the time of arrival of the work piece and assuming no extra idle time on the manufacturer's machine. Based on the different machine capabilities A large number of simulation experiments show the effectiveness of the TP-H algorithm. When the number of workpieces is 1000, the average relative gap of the proposed TP-H algorithm converges to 0.21%, which is superior to the existing MBF algorithm and the MEF algorithm.
(3) the problem of cooperative scheduling of production and transportation is studied. The problem of single machine scheduling in the case of workpiece deterioration is analyzed. The objective functions are to minimize the span time of manufacturing, minimize the number of delayed artifacts and minimize the total completion time of the chemical parts. The problem of cooperative scheduling of production and transportation in the case of cached area is considered, and a corresponding mathematical model is established. The objective function is to minimize the span time of manufacturing. The properties of batch and batch ordering in the optimal scheduling scheme are analyzed, and an optimization algorithm is constructed. In addition, the cooperative scheduling of production and transportation in the case of no cache area is also studied. A mathematical model based on no cache zone constraints is established. The objective function is to minimize the span of manufacturing span. The properties of the optimal solution are analyzed. A new lower boundary is derived and a heuristic algorithm is derived. The simulation experiment results show that the average and maximum relative gap ratio of the heuristic algorithm is less than 0.01 when the number of workpieces is greater than 260. It is.
(4) the problem of cooperative scheduling in production and transportation considering machine failure is studied. A mathematical model is established based on the possible failure of two parallel manufacturer machines. The objective function is to minimize the span time of manufacturing. The properties of the optimal scheduling scheme are analyzed and the lower bounds of the problem are derived. The scheduling rules under two circumstances are constructed, and the scheduling rules are constructed, respectively. These scheduling rules design a new heuristic algorithm. A large number of simulation results show that the heuristic algorithm can efficiently solve different scale problems.
(5) the problem of cooperative scheduling of production and transportation in different geographic locations is studied. A corresponding mathematical model is established based on the characteristics of multiple manufacturers in different geographical locations. The objective function is to minimize the span time of the whole manufacturing process. The optimal solution properties of the problem are analyzed. A novel MGSA algorithm is proposed and the design is designed. The coding correction strategy initializes the population method and the best species group preservation strategy, and puts forward the insertion operation, interchangeability operation and mutation operation. In view of the problem of the work group batch, a hybrid DP-H algorithm combining dynamic programming with heuristic rules is constructed. A large number of simulation results show that the MGSA algorithm is superior to the existing GA and PSO algorithms.

【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP18;F273

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

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本文編號(hào)：1878186