本文關(guān)鍵詞：資源受限下維修任務(wù)網(wǎng)的調(diào)度問題研究　出處：《北京交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 維修保障 資源受限項目調(diào)度 串行進度生成機制 最大最小螞蟻系統(tǒng) 粒子群-遺傳混合算法

【摘要】：裝備維修保障系統(tǒng)是保證裝備保持或恢復(fù)到規(guī)定狀態(tài)的技術(shù)管理活動集合。合理地調(diào)度維修保障活動可以幫助企業(yè)快速解決問題或排除故障,避免事故的發(fā)生,同時還可以保證裝備能夠按時完成規(guī)定任務(wù),對企業(yè)保持工作效率、提升效益有著重要的作用。優(yōu)化調(diào)度維修保障活動中所需資源一直是維修保障系統(tǒng)中的關(guān)鍵性問題。維修任務(wù)網(wǎng)的調(diào)度問題屬于資源受限項目調(diào)度問題。但是由于實際維修環(huán)境的復(fù)雜性,所以經(jīng)典資源受限項目調(diào)度問題的求解算法并不完全適用。本文基于某企業(yè)的現(xiàn)實需求,在經(jīng)典資源受限項目調(diào)度模型的基礎(chǔ)上引入了工位、人員等一系列新的約束條件,設(shè)定最小化最大完工時間為求解目標(biāo),設(shè)計并實現(xiàn)了一個資源約束下維修任務(wù)網(wǎng)的調(diào)度模型,用于解決實際調(diào)度問題。由于精確算法對大規(guī)模問題無法在可接受時間內(nèi)求解,而啟發(fā)式算法可以在較短的時間內(nèi)求得問題的一個較優(yōu)解,所以本文采用啟發(fā)式算法對維修資源受限條件下的調(diào)度優(yōu)化問題進行求解。本文首先使用基于優(yōu)先規(guī)則的構(gòu)造性啟發(fā)式算法,結(jié)合串行進度生成機制對問題模型進行求解,設(shè)計了四類優(yōu)先規(guī)則用于選擇工位、工序、資源和人員。為了進一步優(yōu)化工位、維修人員等資源,本文運用最大最小螞蟻系統(tǒng),通過對信息素的更新加以限制從而實現(xiàn)對工位的選擇的優(yōu)化,其次我們研究了遺傳算法和粒子群算法,并針對本文問題模型,提出了一種基于粒子群和遺傳算法的混合優(yōu)化算法,將遺傳操作因子(選擇、交叉和變異)應(yīng)用到粒子更新規(guī)則上,實現(xiàn)對工位和維修人員兩種資源同時進行優(yōu)化。通過實驗驗證了兩種優(yōu)化算法的優(yōu)化效果,并且通過對比及在仿真軟件中的評估,發(fā)現(xiàn)基于粒子群和遺傳算法的混合優(yōu)化算法具有更優(yōu)的優(yōu)化效果。本文提出的資源約束下維修任務(wù)網(wǎng)的調(diào)度模型是合理的,設(shè)計的求解及優(yōu)化算法能夠得到正確且較優(yōu)的結(jié)果,對改進維修保障作業(yè)有一定的指導(dǎo)作用。
[Abstract]:Equipment maintenance support system is a set of technical management activities to ensure that the equipment is maintained or restored to a specified state. Reasonable dispatch of maintenance support activities can help enterprises solve problems or troubleshoot quickly and avoid accidents. At the same time, it can also ensure that the equipment can complete the prescribed tasks on time, and maintain the efficiency of the enterprise. The resource requirement in optimal scheduling and maintenance support activities is always the key problem in maintenance support system. The scheduling problem of maintenance task network belongs to resource constrained project scheduling problem. The complexity of the actual maintenance environment. Therefore, the classical resource-constrained project scheduling algorithm is not fully applicable. Based on the actual needs of a certain enterprise, the classical resource-constrained project scheduling model based on the introduction of work station. A series of new constraints, such as personnel, set the minimum maximum completion time as the target, and designed and implemented a scheduling model of the maintenance task network under resource constraints. Because the exact algorithm can not solve the large-scale problem in acceptable time, the heuristic algorithm can find a better solution in a short time. Therefore, this paper uses heuristic algorithm to solve the scheduling optimization problem under the condition of limited maintenance resources. Firstly, this paper uses a constructive heuristic algorithm based on priority rules. Combined with the serial schedule generation mechanism to solve the problem model, four kinds of priority rules are designed to select the work, process, resources and personnel. In order to further optimize the work station, maintenance personnel and other resources. In this paper, the maximum and minimum ant system is used to limit the update of pheromone to optimize the work site selection. Secondly, we study the genetic algorithm and particle swarm optimization algorithm, and aim at the model of this paper. A hybrid optimization algorithm based on particle swarm optimization (PSO) and genetic algorithm (GA) is proposed, in which genetic operational factors (selection, crossover and mutation) are applied to particle update rules. The optimization results of the two optimization algorithms are verified by experiments, and the results are compared and evaluated in the simulation software. It is found that the hybrid optimization algorithm based on particle swarm optimization and genetic algorithm has better optimization effect. The scheduling model of maintenance task network under resource constraints proposed in this paper is reasonable. The solution and optimization algorithm can get the correct and better results, which can be used to improve the maintenance support operation.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP18

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