摘要：我国海域面积极为广大，大概为300万平方公里，海岸线的总长度大概为1800公里，一旦发生了事故，会造成人身伤害，而且对社会和经济以及环境也造成很大的负面影响。因此，对海上救援基地布局优化方法的研究无疑对国家救援体系的建设，事故抢救能力和效率的提高具有重要意义。

粒子群算法拥有以下优点，没有变异和交叉运算，依靠粒子速度完成搜索，并且在迭代进化中只有最优的粒子把信息传递给其他粒子，搜索速度快；具有记忆性，粒子群体的历史最好位置可以记忆并传递给其他粒子；需要调整的参数较少，结构简单，易于工程实现；采用实数编码，直接由问题的解决定，问题解的变量数直接作为粒子的维数；因此本课题的选址优化中我们采用的是粒子群算法。

本次研究中，需要考虑的因素非常之多，而且海面非常之广阔。我只选取了一块发生事故比较频繁，长宽各60公里的海域作为研究对象，而且只考虑了经济因素。我把这块海域以及易发生事故地点在坐标上标出来。这块海域易发生事故的地点有七个，需要建设两个救援基地，这两个基地必须覆盖这七个事发地点而且成本尽量低。根据离港口距离的不同，在海上建设基地的成本也不同，离港口越远，建设成本越高，因此我将这块海域按建设成本的不同划分为四个小块，并且在图中按不同的颜色标出来后在图上标上在此块海域建设救援基地的建设成本。

关键词；救援基地，选址优化，粒子群算法，覆盖问题

Abstract：China's sea area is extremely large, about 3 million square kilometers,and the total length of the coastline of about 1800 km, in the event of an accident, will cause personal injury, but also on the social and economic and the environment also caused a great negative impact. Therefore, the study of the optimization method of the layout of the sea rescue base is undoubtedly important to the construction of the national rescue system, the improvement of the rescue capacity and the efficiency of the accident.

Particle swarm algorithm has the following advantages, no mutation and crossover, rely on particle velocity to complete the search, and in the iterative evolution only the best particles to the information passed to other particles, search speed; with memory, the history of the best particles Location can be memorized and passed to other particles; need to adjust the parameters of less structured simple, easy to achieve; using real coding, directly by the solution of the problem, the number of variables directly as the particle dimension; In the site optimization we use the particle swarm optimization algorithm.

In this study, the factors to be considered are very large, and the sea is very broad. I only selected a relatively frequent accident, the length and width of 60 km of the waters as a research object, and only consider the economic factors. I marked the sea and the location of the accident in the coordinates marked out. There are seven locations where the accident is likely to occur in this area, and two rescue bases are needed. These two bases must cover the seven locations and the cost is as low as possible. According to the distance from the port, the cost of building the base at sea is also different from the port farther, the higher the cost of construction, so I will be the waters of the construction costs of the different pided into four small pieces, and in the figure by different The color marked out on the map marked in this block the construction base of the rescue base construction costs.

Key words： rescue base, site optimization, particle swarm algorithm, coverage problem

目录

第一章绪论 1

1.1研究目的及意义 智能算法的海上应急救援基地选址优化设计:http://www.youerw.com/jisuanji/lunwen_204379.html