本文關(guān)鍵詞： 蛙跳算法 場橋 路徑規(guī)劃 遺傳算法 集裝箱堆場　出處：《大連海事大學》2017年碩士論文　論文類型：學位論文

【摘要】：全球經(jīng)濟的飛速發(fā)展使得貿(mào)易運輸業(yè)務(wù)急劇增長。航運在貿(mào)易運輸中占有重要地位,其中集裝箱運輸是航運中最主要的運輸方式之一。集裝箱碼頭為了提高經(jīng)濟效益,需要提高自身的工作效率。而集裝箱堆場場橋的工作效率是影響碼頭整體效率的關(guān)鍵問題之一。解決好場橋路徑規(guī)劃問題,可有效提高集裝箱碼頭的作業(yè)效率,提升碼頭整體效益,從而提高港口的競爭力。本文采用群智能算法求解集裝箱堆場場橋的路徑規(guī)劃問題。在已知集裝箱堆場堆放狀況下,根據(jù)給定的提箱任務(wù),首先建立了以場橋移動距離最短為目標的單臺和多臺場橋的數(shù)學優(yōu)化模型。然后針對該離散組合優(yōu)化問題,研究了一種高效的求解算法�；谳^為新穎的蛙跳算法,對其存在的缺陷加以改進,提出了多種群混合蛙跳算法。其基本思想是采用并行策略,將整個蛙群分為三個子群體,它們分別側(cè)重于向全局最優(yōu)學習以加快收斂速度,和在較優(yōu)個體附近的局部開發(fā)以及全局搜索,維持群體多樣性和防早熟。三者定期進行信息交換,以發(fā)揮各自所長,優(yōu)勢互補,提高算法整體性能。此外,基于遺傳算法的交叉和變異算子的引入能使所提算法適用于求解此類路徑規(guī)劃等離散組合優(yōu)化問題;而與模擬退火思想的混合能夠改善蛙跳算法對最優(yōu)個體附近局部搜索能力的不足,可望進一步加速收斂且有利于防止早熟。為了驗證所提算法的性能,文中將其應用于求解已知最優(yōu)解的經(jīng)典函數(shù)優(yōu)化和旅行商問題,優(yōu)化結(jié)果驗證了其可行性和有效性。在此基礎(chǔ)上,進一步以集裝箱堆場場橋路徑規(guī)劃問題為工程背景,針對所提算法給出了其具體實現(xiàn)的編碼方法,以及交叉和變異策略。將所提算法應用于前述數(shù)學優(yōu)化模型之中,進行仿真與測試,分別求解了針對兩個實例的單臺場橋和多臺場橋的路徑規(guī)劃問題,并對結(jié)果進行了分析和對比。研究表明,提出的算法對于該路徑規(guī)劃問題是有效的,獲得了較好的優(yōu)化結(jié)果,所得的場橋路徑規(guī)劃方案,工程適用且令人滿意。本文的工作能夠為集裝箱堆場場橋的實際作業(yè)操作提供參考和借鑒,以達到提高碼頭的作業(yè)效率和經(jīng)濟效益的目的。研究具有一定的理論意義和實用價值。
[Abstract]:With the rapid development of the global economy, trade and transportation business is growing rapidly. Shipping plays an important role in trade transportation, among which container transportation is one of the most important transportation modes. The efficiency of the container yard bridge is one of the key problems affecting the overall efficiency of the terminal. To solve the problem of the route planning of the yard bridge can effectively improve the operational efficiency of the container terminal. In this paper, we use swarm intelligence algorithm to solve the path planning problem of container yard bridge. Under the condition of known container yard stacking, according to the given container task, Firstly, the mathematical optimization models of single and multiple field bridges with the shortest moving distance are established. Then, an efficient algorithm for solving the discrete combinatorial optimization problem is proposed, which is based on a novel leapfrog algorithm. In order to improve its shortcomings, a multi-group hybrid leapfrog algorithm is proposed. The basic idea is to divide the whole frog population into three subpopulations by using parallel strategy, which respectively focus on learning to the global optimum to speed up the convergence rate. And local development in the vicinity of superior individuals and global search to maintain population diversity and prevent precocity. The three regularly exchange information to give play to their respective strengths, complement each other, and improve the overall performance of the algorithm. The introduction of crossover and mutation operators based on genetic algorithm can make the proposed algorithm suitable for solving such discrete combinatorial optimization problems as path planning. Mixing with simulated annealing can improve the local search ability of the leapfrog algorithm near the optimal individual, which is expected to accelerate convergence and prevent precocity. In order to verify the performance of the proposed algorithm, In this paper, it is applied to the classical function optimization and traveling salesman problem of known optimal solution. The optimization results verify its feasibility and effectiveness. On this basis, the engineering background of the bridge path planning problem of container yard is further taken as the engineering background. The coding method, crossover and mutation strategy of the proposed algorithm are given. The proposed algorithm is applied to the above mathematical optimization model for simulation and test. The path planning problem of single field bridge and multi field bridge with two examples is solved, and the results are analyzed and compared. The results show that the proposed algorithm is effective for the path planning problem, and good optimization results are obtained. The project is applicable and satisfactory. The work in this paper can provide reference and reference for the practical operation of the container yard bridge. In order to improve the efficiency and economic benefit of the wharf, the research has certain theoretical significance and practical value.
【學位授予單位】：大連海事大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U691.3;TP18

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