基于改进蚁群算法的船台吊装顺序优化技术研究
发布时间：2018-09-05 16:01
【摘要】：船舶业的发展对于国防建设和海洋主权完整有着重要的战略意义,也为海上运输、海洋资源勘探等提供了雄厚的技术支持。2010伊始,我国作为海洋大国,不但在航运总量上名列前茅,造船总量也跃居全球第一。“十二五”时期,全球经济利益格局动荡,船舶市场竞争更加激烈,如何提高造船效率是各个船厂应对激烈竞争的重要挑战之一。船台吊装是船舶建造的重要环节,船台(船坞)是船厂不可替代的重要设施资源,可以说船台(船坞)的数量和尺寸最直接体现了船厂的生产能力。所以,通过对船台(船坞)吊装方案的最优化,提高船台(船坞)资源的利用率,对缩短船台周期意义十分重大。 船台吊装顺序优化的问题是典型NP难题,仅通过人工经验很难获得最佳的方案。对此,本文以蚁群优化算法(ACO)为基础,根据资源受限的调度理论(RCPSP),对船台吊装顺序的优化进行研究,具体内容如下： 笔者首先对国内外船台调装调度问题和RCPSP问题的研究动态做出详细的总结梳理,同时基于ACO的基本原理,加之对于船台吊装特点的结合,对算法进行了改进,已达到该算法在优化船台吊装顺序过程中的性能要求,使之能够发挥优良效果。 给出船台吊装调度系统整体框架和功能,并对分段信息的数据结构的和吊装网络图的构建进行了研究。 在多资源的约束条件下,以RCPSP资源有限-工期最短模型为基础,结合船台吊装顺序优化的特点,建立单船船台吊装和多船船台吊装问题的数学模型,并给出了模型的改进蚁群优化方法。 最后应用本文提出的改进蚁群算法分别优化大连造船厂某船台的单船吊装和多船吊装的方案,求解最短吊装工期和最优的吊装计划,并分析了资源的调度分配和算法的优化性能,证明采用本方法来优化船台吊装顺序是合理可行的。
[Abstract]:The development of ship industry has important strategic significance for national defense construction and maritime sovereignty integrity, and also provides abundant technical support for marine transportation and marine resource exploration. At the beginning of 2010, our country is a large marine country. Not only in the total shipping volume, shipbuilding volume also leapt to the first in the world. During the 12th Five-Year Plan period, the global economic benefit pattern is turbulent, and the competition in ship market is more intense. How to improve shipbuilding efficiency is one of the important challenges for shipyards to cope with fierce competition. Platform hoisting is an important link in ship construction, and the shipyard (dock) is an irreplaceable important facility resource. It can be said that the quantity and size of the berth (dock) directly reflect the production capacity of the shipyard. Therefore, it is of great significance to shorten the period of the platform by optimizing the hoisting scheme of the platform (dock) and improving the utilization ratio of the resources of the platform (dock). The optimization of hoisting sequence is a typical NP problem, and it is difficult to obtain the best scheme only through artificial experience. In this paper, based on ant colony optimization algorithm (ACO) and resource constrained scheduling theory (RCPSP), the optimization of ship platform hoisting sequence is studied. The specific contents are as follows: firstly, the author summarizes and combs the research trends of the domestic and foreign ship platform adjustment and installation scheduling problem and RCPSP problem in detail, at the same time, based on the basic principle of ACO, in addition to the combination of the characteristics of the platform hoisting, The algorithm has been improved to meet the performance requirements of the algorithm in the process of optimizing the order of hoisting of the ship platform, so that it can play a good effect. The whole frame and function of the platform hoisting and dispatching system are given, and the construction of the data structure and the hoisting network diagram of the segmented information are studied. Under the constraint of multiple resources, the mathematical models of single ship platform hoisting and multi-ship platform hoisting are established on the basis of RCPSP resource finite-duration shortest model and combined with the characteristics of ship platform hoisting sequence optimization. An improved ant colony optimization method is presented. Finally, the improved ant colony algorithm proposed in this paper is applied to optimize the single ship hoisting and multi-ship hoisting of a shipyard in Dalian Shipyard, and to solve the shortest hoisting period and the optimal hoisting plan. The scheduling and allocation of resources and the optimization performance of the algorithm are analyzed. It is proved that this method is reasonable and feasible to optimize the order of ship platform hoisting.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U673.31;TP18
本文编号：2224763
[Abstract]:The development of ship industry has important strategic significance for national defense construction and maritime sovereignty integrity, and also provides abundant technical support for marine transportation and marine resource exploration. At the beginning of 2010, our country is a large marine country. Not only in the total shipping volume, shipbuilding volume also leapt to the first in the world. During the 12th Five-Year Plan period, the global economic benefit pattern is turbulent, and the competition in ship market is more intense. How to improve shipbuilding efficiency is one of the important challenges for shipyards to cope with fierce competition. Platform hoisting is an important link in ship construction, and the shipyard (dock) is an irreplaceable important facility resource. It can be said that the quantity and size of the berth (dock) directly reflect the production capacity of the shipyard. Therefore, it is of great significance to shorten the period of the platform by optimizing the hoisting scheme of the platform (dock) and improving the utilization ratio of the resources of the platform (dock). The optimization of hoisting sequence is a typical NP problem, and it is difficult to obtain the best scheme only through artificial experience. In this paper, based on ant colony optimization algorithm (ACO) and resource constrained scheduling theory (RCPSP), the optimization of ship platform hoisting sequence is studied. The specific contents are as follows: firstly, the author summarizes and combs the research trends of the domestic and foreign ship platform adjustment and installation scheduling problem and RCPSP problem in detail, at the same time, based on the basic principle of ACO, in addition to the combination of the characteristics of the platform hoisting, The algorithm has been improved to meet the performance requirements of the algorithm in the process of optimizing the order of hoisting of the ship platform, so that it can play a good effect. The whole frame and function of the platform hoisting and dispatching system are given, and the construction of the data structure and the hoisting network diagram of the segmented information are studied. Under the constraint of multiple resources, the mathematical models of single ship platform hoisting and multi-ship platform hoisting are established on the basis of RCPSP resource finite-duration shortest model and combined with the characteristics of ship platform hoisting sequence optimization. An improved ant colony optimization method is presented. Finally, the improved ant colony algorithm proposed in this paper is applied to optimize the single ship hoisting and multi-ship hoisting of a shipyard in Dalian Shipyard, and to solve the shortest hoisting period and the optimal hoisting plan. The scheduling and allocation of resources and the optimization performance of the algorithm are analyzed. It is proved that this method is reasonable and feasible to optimize the order of ship platform hoisting.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U673.31;TP18
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