本文選題：不確定環(huán)境 + 重調(diào)度執(zhí)行成本�。� 參考：《合肥工業(yè)大學(xué)》2012年碩士論文

【摘要】：現(xiàn)有關(guān)于重調(diào)度驅(qū)動機制的研究中，周期性重調(diào)度、事件驅(qū)動重調(diào)度以及兩者相混合的重調(diào)度雖已得到廣泛的應(yīng)用，但周期性重調(diào)度缺乏對突發(fā)事件的應(yīng)變能力，與實時工況的耦合性不強，事件驅(qū)動的重調(diào)度易導(dǎo)致系統(tǒng)計算量過大、增大重調(diào)度頻率、引起系統(tǒng)震蕩，，而混合驅(qū)動重調(diào)度則很難協(xié)調(diào)事件驅(qū)動與周期驅(qū)動之間的關(guān)系。因此本課題以加強實時工況與調(diào)度系統(tǒng)的耦合性、增強系統(tǒng)穩(wěn)定性以及最大化企業(yè)效益為目標，研究不確定環(huán)境下Job Shop制造車間的重調(diào)度驅(qū)動機制。 首先分析歸類Job Shop制造車間生產(chǎn)過程中面臨的不確定因素，并通過模糊數(shù)學(xué)與徑向基神經(jīng)網(wǎng)絡(luò)相結(jié)合的方法，量化其對調(diào)度系統(tǒng)的擾動程度；然后通過綜合加權(quán)相同工序的時間偏差成本、相同工件的相鄰工序的時間偏差成本、設(shè)備的工作時間偏差成本以及等待時間偏差成本，實現(xiàn)對重調(diào)度執(zhí)行成本的衡量，并以此為基礎(chǔ)建立預(yù)調(diào)度損失函數(shù)，同時根據(jù)重調(diào)度的優(yōu)化目標建立預(yù)調(diào)度獲益函數(shù)，構(gòu)建損益模型；最后通過對損益模型的定量分析研究，建立基于模糊邏輯的重調(diào)度驅(qū)動機制，判斷重調(diào)度的最佳決策點，以此過濾不必要的重調(diào)度，解決因頻繁重調(diào)度而引起的生產(chǎn)系統(tǒng)震蕩問題，降低各種不確定性問題給生產(chǎn)系統(tǒng)帶來的損失，保證調(diào)度系統(tǒng)的有效性與穩(wěn)定性。
[Abstract]:Although periodic rescheduling, event-driven rescheduling and mixed rescheduling have been widely used in the research of rescheduling drive mechanism, periodic rescheduling lacks the ability to respond to emergencies. The coupling with real-time conditions is not strong, and event-driven rescheduling can easily lead to excessive calculation, increase the frequency of rescheduling and cause system oscillation, while hybrid driven rescheduling is very difficult to coordinate the relationship between event-driven and periodic drive. Therefore, in order to enhance the coupling between real-time operation and scheduling system, enhance the stability of the system and maximize the efficiency of the enterprise, this paper studies the rescheduling driving mechanism of Job Shop manufacturing shop in uncertain environment. Firstly, the uncertain factors in the production process of Job Shop manufacturing workshop are analyzed and classified, and the disturbance degree of the scheduling system is quantified by combining fuzzy mathematics with radial basis function neural network. Then, by synthetically weighting the cost of time deviation of the same working procedure, the cost of time deviation of adjacent processes of the same workpiece, the cost of working time deviation of equipment and the cost of waiting time deviation, the cost of rescheduling execution is measured. On this basis, the loss function of pre-scheduling is established, and the profit function of pre-scheduling is established according to the optimization goal of rescheduling, and the profit and loss model is constructed. Finally, the quantitative analysis of profit and loss model is carried out. The rescheduling driving mechanism based on fuzzy logic is established to judge the optimal decision point of rescheduling so as to filter unnecessary rescheduling and solve the problem of production system shock caused by frequent rescheduling. Reduce the loss of production system caused by various uncertainty problems, and ensure the efficiency and stability of scheduling system.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：TH186

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本文編號：1952223