共查询到18条相似文献,搜索用时 78 毫秒
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武斌 《胜利油田师范专科学校学报》2014,(3):23-25
针对组合优化中的TSP问题,分析了遗传算法的特点,设计了遗传算法的编码、交叉、变异及进化逆转算子,克服了遗传算法容易出现局部收敛的现象,并使用Matlab实现了这一算法,将其应用于山东省17个城市的TSP问题,通过计算结果分析验证了该遗传算法的有效性。 相似文献
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武斌 《中国石油大学胜利学院学报》2014,(3)
针对组合优化中的TSP问题,分析了遗传算法的特点,设计了遗传算法的编码、交叉、变异及进化逆转算子,克服了遗传算法容易出现局部收敛的现象,并使用Matlab实现了这一算法,将其应用于山东省17个城市的TSP问题,通过计算结果分析验证了该遗传算法的有效性。 相似文献
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翟梅梅 《淮南师范学院学报》2009,11(5):114-119
遗传算法容易产生早熟现象以及局部寻优能力较差的缺陷。针对遗传算法的这一缺点,就遗传算法的交叉算子进行改进.并应用于求解旅行商问题。传统的交叉算子操作方法寻优效率低,并易陷入局部最优,就顺序交叉方法进行改进。改进后的交叉算子是在随机选择交叉区域和交叉片断长度后.对重复节点和前后节点的路径长度进行比较后,再删除路径长的重复节点,有效地提高了算法的寻优效率。优化了解的质量。为了验证算法的有效性,对TSPLIB库中的两个公共实际事例ei151和gr202以及安徽省17个城市的数据进行了仿真实验。结果表明改进后的算法是有效的. 相似文献
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利用基本遗传算法的思路解决旅行商问题,选择仍然采用轮盘选择方法;交叉算法采用一个启发式交叉算法,交叉位置随机,该算法以一定的概率生成一个比父代好的解,交叉概率取0.1;变异概率0.005。经多次运行,求得最优值。停止法则为循环最大遗传代数为止,另外如果30代解没有改进则停止。编程环境为Mat-lab6.5。 相似文献
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炎士涛 《河南科技学院学报》2010,38(1)
遗传算法(GA)是由遗传进化理论指导的随机搜索寻优算法,传统GA的寻优能力与随机搜索能力之间存在着相互制约的关系,所以对地形极其复杂、极无规律的TSP的应用效果并不十分理想.通过利用互换启迪交叉算子加快局部搜索算法的收敛速度,利用模式增加修补算子防止算法早熟收敛,给出了一种求解TSP问题的新型遗传算法.仿真实验表明该算法是有效的和可行的. 相似文献
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缪桂根 《楚雄师范学院学报》2011,26(3):5-10
本文用改进遗传算法求解TSP问题,编制了完整的Matlab程序予以仿真实现。程序中选择算子使用的是最佳个体保存与赌轮选择相结合的策略,文章最后分析了最佳个体保持比例对寻优效果的影响。 相似文献
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方铖 《四川教育学院学报》2008,24(1):110-112
遗传算法是一种模拟自然界生物进化过程的随机搜索算法;遗传算法目前已经在组合优化、机器学习和并行处理等领域得到了越来越广泛的应用;文章对遗传算法的理论与应用进行了一些研究和分析,介绍了遗传算法的理论,以及它在鸭P问题中的应用。 相似文献
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基于遗传算法求解TSP问题的算法设计 总被引:2,自引:0,他引:2
TSP是一个典型的组合优化问题,并且是一个NP难题,其可能的路径总数与城市数目n是成指数型增长的,所以一般很难精确地求出其最优解,因而寻找出有效的近似求解算法就具有重要的意义.现提出一种求解TSP问题比较有效的遗传算法,从其数学模型、遗传算子、评估函数、种群多样性等方面对算法进行了分析,结果表明提出的算法在求解TSP问题上是有效的. 相似文献
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Gong Qu He Xian-yang 《重庆大学学报(英文版)》2005,4(4):229-232
In this paper, recent developments of some heuristic algorithms were discussed. The focus was laid on the improvements of ant-cycle (AC) algorithm based on the analysis of the performances of simulated annealing (SA) and AC for the traveling salesman problem (TSP). The Metropolis rules in SA were applied to AC and turned out an improved AC. The computational results obtained from the case study indicated that the improved AC algorithm has advantages over the sheer SA or unmixed AC. 相似文献
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Genetic algorithms (GAs) employ the evolutionary process of Darwin's nature selection theory to find the solutions of optimization problems. In this paper, an implementation of genetic algorithm is put forward to solve a classical transportation problem, namely the Hitchcock's Transportation Problem (HTP), and the GA is improved to search for all optimal solutions and identify them automatically. The algorithm is coded with C and validated by numerical examples. The computational results show that the algorithm is efficient for solving the Hitchcock's transportation problem. 相似文献
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This paper presents a new genetic algorithm for the resource-constrained project scheduling problem(RCPSP).The algorithm employs a standardized random key(SRK) vector representation with an additional gene that determines whether the serial or parallel schedule generation scheme(SGS) is to be used as the decoding procedure.The iterative forward-backward improvement as the local search procedure is applied upon all generated solutions to schedule the project three times and obtain an SRK vector,which is rese... 相似文献
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A new algorithm is presented by using the ant colony algorithm based on genetic method (ACG) to solve the continuous optimization problem.Each component has a seed set.The seed in the set has the value of component,trail information and fitness.The ant chooses a seed from the seed set with the possibility determined by trail information and fitness of the seed.The genetic method is used to form new solutions from the solutions got by the ants.Best solutions are selected to update the seeds in the sets and trail information of the seeds.In updating the trail information,a diffusion function is used to achieve the diffuseness of trail information.The new algorithm is tested with 8 different benchmark functions. 相似文献
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提出了一种求解0-1背包问题的遗传算法,该算法首先设计出基于适应度的自适应变异策略,提高了变异的科学性和新算法的搜索能力;然后提出了基于单位价值信息和满足约束最大化的双优化策略,提高了求解的质量.3个0-1背包问题的仿真实验表明:与已有的HGA算法和GGA算法相比,新算法在求解质量上具有一定优势. 相似文献
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肖剑 《重庆大学学报(英文版)》2005,4(1):59-62
1 Introduction a The bi-level decision-making is a complex majorized problem. Its effective solution is not easy to obtain by traditional majorized methods. Reported methods to solve the bi-level decision making problem with continuous variables include neural network [1], Monte Carlo simulated annealing algorithm [2], etc. However, the efficiency and accuracy of such neural network methods are ideal and accompanied with a long iterative time and a slow convergence speed. In this paper, the … 相似文献
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The context of the study presented in this paper is a sixth-semester undergraduate course on “Relational database management system” that was held in session 2009–2010. The course is part of the bachelor’s degree curriculum of Computer Science and Engineering branch at Punjab Technical University, Punjab, India. It consists of a lecture course and a concurrent lab course. The common approach has been to divide the course into lectures, tutorials, and practicals. To conduct practical sessions, lab plan is prepared beforehand by the faculty. The course duration is 14–16 weeks. Here the lab course was conducted in a blended learning mode, starting with syllabus related tasks, then subject specific projects, and presenting team project results. Problem based learning (PBL) and Blogging have been introduced for practical sessions. This paper describes this novel approach in which problems are designed to cover the syllabus topics, and blogging is used to bridge the communication gap. A significant difference was seen between performance and attitude of the treatment group (PBL with blogging) and control group (only PBL) for Lab sessions. Additionally teamwork and communication skills were also significantly improved in the case of PBL with blogging class. 相似文献
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使用中流量TSP采样器对喀什市TSP进行了监测,采用火焰原子吸收分光光度法对TSP中的铅、镉等重金属元素进行了分析,并对大气污染状况进行评价.结果表明,喀什市TSP含量存在超标现象. 相似文献