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布谷鸟搜索算法是一种新型元启发式优化算法,该算法受到自然界中布谷鸟的巢寄生行为启发而提出。首先分析了布谷鸟搜索算法的仿生原理和数学描述,采用基于工序的编码方式对最小化最大完工时间的作业车间调度问题进行布谷鸟搜索算法求解。通过典型算例进行仿真实验,测试结果表明布谷鸟搜索算法求解作业车间调度问题的可行性和有效性,优于萤火虫算法和基本粒子群算法,是解决生产调度问题的一种有效方法。 相似文献
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《计算机应用与软件》2016,(6)
针对作业车间调度问题JSP(Job-shop scheduling problem),提出一种入侵式杂草优化算法。该算法中,子代以正态分布方式在父代个体周围扩散,兼顾全局搜索和局部搜索,并根据迭代次数不同对二者强度进行调节。通过典型算例进行仿真试验,并在反复实验中对算法参数进行修正。测试结果表明杂草算法求解作业车间调度问题的可行性和有效性,优于萤火虫算法和基本粒子群算法,是解决生产调度问题的一种有效方法。 相似文献
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制造企业的成本优化,无论在学术界还是工业界,始终是一个热点研究课题。从成本优化思想出发,建立了基于成本的多产品切换作业车间调度问题的经济指标模型,并应用具有新型交叉、变异算子的遗传算法作为求解该调度问题的方法,其目的是使企业的综合生产成本(主要包括多产品切换成本、产品作为在制品的存储成本以及产品拖期惩罚等)最低。仿真实例的运行结果表明了该调度模型和优化算法的有效性,且适用于过程工业及离散工业的生产调度系统,实现生产调度和经济效益的有效集成。 相似文献
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为了解决车间作业调度问题,在对其进行分析描述的基础上,提出了采用蜜蜂交配优化算法的求解方法。该方法把由多个作业调度方案组成的集合作为蜂群,以最小化加工时间作为算法的优化目标,通过模拟蜂群交配繁衍培养蜂王的优化过程来获得最优作业调度方案。采用车间作业调度测试案例在Matlab平台上进行实验,实验结果表明,该方法不仅能够有效地求解车间作业调度问题,而且能够取得了比传统优化方法更好的优化结果。 相似文献
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提出了用于解决作业车间调度问题的离散版粒子群优化算法。该算法采用基于先后表编码方案和新的位移更新模型,使具有连续本质的粒子群优化算法直接适用于车间调度问题。同时,利用粒子群优化算法的全局搜索能力和禁忌搜索算法的自适应优点,将粒子群优化算法和禁忌搜索结合起来,设计了广义粒子群优化算法和粒子群—禁忌搜索交替算法两种混合调度算法。实验结果表明,两种混合调度算法能够有效地、高质量地解决作业车间调度问题。 相似文献
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Fuh-Der Chou Tzu-Yun Chang Ching-En Lee 《International Transactions in Operational Research》2005,12(2):215-233
This paper attempts to solve a single machine‐scheduling problem, in which the objective function is to minimize the total weighted tardiness with different release dates of jobs. To address this scheduling problem, a heuristic scheduling algorithm is presented. A mathematical programming formulation is also formulated to validate the performance of the heuristic scheduling algorithm proposed herein. Experimental results show that the proposed heuristic algorithm can solve this problem rapidly and accurately. Overall, this algorithm can find the optimal solutions for 2200 out of 2400 randomly generated problems (91.67%). For the most complicated 20 job cases, it requires less than 0.0016 s to obtain an ultimate or even optimal solution. This heuristic scheduling algorithm can therefore efficiently solve this kind of problem. 相似文献
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This paper investigates a single-machine deteriorating job scheduling problem with job release times where its objective is to minimize the makespan. The problem is known to be NP-hard. Therefore, a branch-and-bound algorithm incorporating with several dominance properties and lower bounds is proposed to derive the optimal solution for the problem. In addition, easy-implemented heuristic algorithms are also provided to obtain the near-optimal solution. The computational experiments indicate that the branch-and-bound algorithm can solve most of the medium-job-sized problems within a reasonable time, and the heuristic is quite accurate with an average error percentage of less than 0.3%. 相似文献
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This paper examines the problem of scheduling two-machine no-wait job shops to minimize makespan. The problem is known to be strongly NP-hard. A two-phase heuristic is developed to solve the problem. Phase 1 of the heuristic transforms the problem into a no-wait flow shop problem and solves it using the well known Gilmore and Gomory algorithm. Phase 2 of the heuristic improves the solution obtained in phase 1 using a simple tabu search algorithm. Computational results show that the proposed heuristic performs extremely well in terms of both solution quality and computation time. It finds an optimal solution to about 90% of the problem instances and the average deviation from the lower bond for the other problem instances is infinitesimal. 相似文献
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加权圆集布局问题是基于性能驱动的一类布局问题,由于其NP-hard属性,难以在多项式时间内求解,提出一种快速启发式搜索算法。权矩阵的行向量1范数作为首次赌轮选择圆的启发信息,依次以权矩阵的当前行(其行号等于当前选择圆的序号)元素作为下次赌轮选择的启发信息,利用图形学理论给出低计算复杂度的定位规则,进而基于该定序定位规则提出一种启发式搜索算法,以求得该问题的最优解。数值实验表明,该算法的性能优于已有算法。 相似文献
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This paper studies the layout optimization problem with equilibrium constraint. It is a two-dimensional packing problem with the industrial background of simplified satellite module layout design, and is known as NP-hard problem. By incorporating the heuristic neighborhood search mechanism and the adaptive gradient method into the simulated annealing procedure, a heuristic simulated annealing algorithm is put forward for this problem. The special neighborhood search mechanism can avoid the disadvantage of blind search in the simulated annealing algorithm, and the adaptive gradient method is used to execute local search and speed up finding the global optimal solution. Numerical examples are illustrated to verify the effectiveness of the proposed algorithm. 相似文献
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《Computers & Industrial Engineering》2011,60(4):530-536
This paper studies the layout optimization problem with equilibrium constraint. It is a two-dimensional packing problem with the industrial background of simplified satellite module layout design, and is known as NP-hard problem. By incorporating the heuristic neighborhood search mechanism and the adaptive gradient method into the simulated annealing procedure, a heuristic simulated annealing algorithm is put forward for this problem. The special neighborhood search mechanism can avoid the disadvantage of blind search in the simulated annealing algorithm, and the adaptive gradient method is used to execute local search and speed up finding the global optimal solution. Numerical examples are illustrated to verify the effectiveness of the proposed algorithm. 相似文献
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This paper introduces a tabu search heuristic for a production scheduling problem with sequence-dependent and time-dependent
setup times on a single machine. The problem consists in scheduling a set of dependent jobs, where the transition between
two jobs comprises an unrestricted setup that can be performed at any time, and a restricted setup that must be performed
outside of a given time interval which repeats daily in the same position. The setup time between two jobs is thus a function
of the completion time of the first job. The tabu search heuristic relies on shift and swap moves, and a surrogate objective
function is used to speed-up the neighborhood evaluation. Computational experiments show that the proposed heuristic consistently
finds better solutions in less computation time than a recent branch-and-cut algorithm. Furthermore, on instances where the
branch-and-cut algorithm cannot find the optimal solution, the heuristic always identifies a better solution. 相似文献
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The Rapidly-exploring Random Tree (RRT) algorithm is an efficient path-planning algorithm based on random sampling. The RRT* algorithm is a variant of the RRT algorithm that can achieve convergence to the optimal solution. However, it has been proven to take an infinite time to do so. An improved Quick-RRT* (Q-RRT*) algorithm based on a virtual light source is proposed in this paper to overcome this problem. The virtual light-based Q-RRT* (LQ-RRT*) takes advantage of the heuristic information generated by the virtual light on the map. In this way, the tree can find the initial solution quickly. Next, the LQ-RRT* algorithm combines the heuristic information with the optimization capability of the Q-RRT* algorithm to find the approximate optimal solution. LQ-RRT* further optimizes the sampling space compared with the Q-RRT* algorithm and improves the sampling efficiency. The efficiency of the algorithm is verified by comparison experiments in different simulation environments. The results show that the proposed algorithm can converge to the approximate optimal solution in less time and with lower memory consumption. 相似文献
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公共交货期窗口下提前/拖期问题的多机调度算法 总被引:2,自引:1,他引:1
提出了求公共交货期窗口下提前/拖期都有惩罚的单机零件排序问题最优解的新算法,建立了相应多机零件排序问题的数学模型。在证明关于单机问题最优排序和最优公共交货期性质的若干定理的基础上,给出了求解多机问题的一个启发式算法。数值例子表明,该算法有较为理想的优化效果和工程实用价值。 相似文献
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The multiple destination routing (MDR) problem can be formulated as finding a minimal cost tree which contains designated source and multiple destination nodes so that certain constraints in a given communication network are satisfied. This is a typical NP-hard problem, and therefore only heuristic algorithms are of practical value. As a first step, a new genetic algorithm is developed to solve the MDR problems without constraints. It is based on the transformation of the underlying network of an MDR problem into its distance complete form, a natural chromosome representation of a minimal spanning tree (an individual), and a completely new computation of the fitness of individual. Compared with the known genetic algorithms and heuristic algorithms for the same problem, the proposed algorithm has several advantages. First, it guarantees convergence to an optimal solution with probability one. Second, not only are the resultant solutions all feasible, the solution quality is also much higher than that obtained by the other methods (indeed, in almost every case in our simulations, the algorithm can find the optimal solution of the problem). Third, the algorithm is of low computational complexity, and this can be decreased dramatically as the number of destination nodes in the problem increases. The simulation studies for the sparse and dense networks all demonstrate that the proposed algorithm is highly robust and very efficient in the sense of yielding high-quality solutions 相似文献