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基于自适应模拟退火遗传算法的传感器优化配置研究 总被引:2,自引:0,他引:2
针对传感器优化配置组合优化问题,提出了一种基于模态置信度准则MAC的优化算法——自适应模拟退火遗传算法。以模态置信度MAC矩阵的最大非对角元的值极小为目标函数,针对满足传感器数量不变的约束条件问题,提出了二重结构编码遗传算法,并将传统的模拟退火算法改良后,作为一个独立的算子置于遗传算法进化过程中;为了避免出现过早收敛的现象,引入了自适应交叉和变异概率。算例结果表明该混合算法对传感器数目与位置同时实现了优化,得到了满足不同精度要求的传感器优化配置方案。 相似文献
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对遗传模拟退火算法中的交叉、变异操作进行了改进,并实施了最优保留策略,形成了改进遗传模拟退火算法.以突击效果最大化和兵力损失最小化为目标函数,以空袭兵力总量的限制、空袭兵器挂载类型的限制等为约束条件,建立了空袭兵力分配及优化模型.在考虑兵力分配模型特点的基础上,利用改进遗传模拟退火算法求解.通过与多目标数学规划和标准遗传算法优化进行的比较表明,该方法能够有效地解决带约束的多目标优化问题. 相似文献
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多目标规划是一类重要的优化模型,有着广泛的实际应用,但其求解至今仍是运筹学的一个难点.针对一般约束多目标优化问题,在设计了新的适应度函数和选择算子的基础上,提出一种新型多目标遗传算法.将其应用于导弹对集群目标射击效能优化问题,验证了算法的有效性. 相似文献
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为解决混流产品在无等待多条流水线生产条件下,由于产品生产节拍不一致导致总装分装系统中生产连续性较差的问题,研究总装分装任务排序优化方法,实现在保证批量生产、部件齐套供应前提下,使订单能够按期交货.以最小化总加工时间、最小化总提前/拖期和产品转换惩罚为优化目标,建立了优化数学模型,并设计了改进多种群蚁群算法求解该优化模型.以某机床厂某月生产任务为例进行仿真实验,与多种群蚁群算法、传统蚁群算法对比,验证了该算法性能较好.并与现行的调度方法进行对比,验证了该任务排序方法在混流节拍不一致的多条装配线生产上,能够有效地缩短产品生产周期、降低生产成本,提高订单的准时交付率. 相似文献
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为了解决并联机器人机构的优化设计问题,提出一种基于正交试验设计法和遗传算法的优化方法。在简要讨论正交试验设计法和遗传算法的基本原理基础上,对两种方法的寻优算法、各个参数的对应关系作了比较分析,探讨了用正交表构造遗传算法中初始种群的方法。提出一种适用于设计变量多且适应度函数难求的“一代”正交-遗传试验法的思路和方法。将该方法应用于一种新型四自由度并联机器人机构的结构优化设计,得出以机构全域条件数为目标函数的机构结构优化尺寸方案。实例证明这种优化方法行之有效。 相似文献
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在印制电路板钻孔任务调度等工程实际中,普遍存在一类具有任务拆分特性与簇准备时间的并行机调度问题,尚缺乏高效的优化模型和方法。针对该问题,首先建立以总拖期最小为目标的数学模型,以约束的形式将两个现有优势定理嵌入其中。为了高效求解实际规模问题,进一步提出嵌入优势定理的模拟退火算法。最后,基于随机生成的算例构造计算实验,以验证所建模型和算法的有效性。实验结果表明,嵌入优势定理的数学模型在问题求解规模和计算效率方面均优于现有数学模型,嵌入优势定理的模拟退火算法同样优于现有模拟退火算法。 相似文献
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Yu-Wei An 《国际生产研究杂志》2016,54(22):6718-6735
This paper focuses on simultaneous optimisation of production planning and scheduling problem over a time period for synchronous assembly lines. Differing from traditional top-down approaches, a mixed integer programming model which jointly considers production planning and detailed scheduling constraints is formulated, and a Lagrangian relaxation method is developed for the proposed model, whereby the integrated problem is decomposed into planning, batch sequencing, tardiness and earliness sub-problems. The scheduling sub-problem is modelled as a time-dependent travelling salesman problem, which is solved using a dynasearch algorithm. A proposition of Lagrangian multipliers is established to accelerate the convergence speed of the proposed algorithm. The average direction strategy is employed to solve the Lagrangian dual problem. Test results demonstrate that the proposed model and algorithm are effective and efficient. 相似文献
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This article presents the first method to simultaneously balance and sequence robotic mixed-model assembly lines (RMALB/S), which involves three sub-problems: task assignment, model sequencing and robot allocation. A new mixed-integer programming model is developed to minimize makespan and, using CPLEX solver, small-size problems are solved for optimality. Two metaheuristics, the restarted simulated annealing algorithm and co-evolutionary algorithm, are developed and improved to address this NP-hard problem. The restarted simulated annealing method replaces the current temperature with a new temperature to restart the search process. The co-evolutionary method uses a restart mechanism to generate a new population by modifying several vectors simultaneously. The proposed algorithms are tested on a set of benchmark problems and compared with five other high-performing metaheuristics. The proposed algorithms outperform their original editions and the benchmarked methods. The proposed algorithms are able to solve the balancing and sequencing problem of a robotic mixed-model assembly line effectively and efficiently. 相似文献
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介绍了装配线平衡问题的传统模型,分析了传统启发式算法与遗传算法在解决现今生产中的大规模带复杂任务约束问题时的弊端.针对传统模型的局限性,给出了修正模型,然后集合数种组合优化算法的优点,对传统启发式算法的候选规则与任务分配规则进行改进,给出了一种可行、高效率的优化算法,最后用实例验证了算法的优良性能. 相似文献
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The mixed model assembly line is becoming more important than the traditional single model due to the increased demand for higher productivity. In this paper, a set of procedures for mixed-model assembly line balancing problems (MALBP) is proposed to make it efficiently balance. The proposed procedure based on the meta heuristics genetic algorithm can perform improved and efficient allocation of tasks to workstations for a pre-specified production rate and address some particular features, which are very common in a real world mixed model assembly lines (e.g. use of parallel workstations, zoning constraints, resource limitation). The main focus of this study is to study and modify the existing genetic algorithm framework. Here a heuristic is proposed to reassign the tasks after crossover that violates the constraints. The new method minimises the total number of workstation with higher efficiency and is suitable for both small and large scale problems. The method is then applied to solve a case of a plastic bag manufacturing company where the minimum number of workstations is found performing more efficiently. 相似文献
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Topology optimization of fluid problems using genetic algorithm assisted by the Kriging model 下载免费PDF全文
M. Yoshimura K. Shimoyama T. Misaka S. Obayashi 《International journal for numerical methods in engineering》2017,109(4):514-532
A non‐gradient‐based approach for topology optimization using a genetic algorithm is proposed in this paper. The genetic algorithm used in this paper is assisted by the Kriging surrogate model to reduce computational cost required for function evaluation. To validate the non‐gradient‐based topology optimization method in flow problems, this research focuses on two single‐objective optimization problems, where the objective functions are to minimize pressure loss and to maximize heat transfer of flow channels, and one multi‐objective optimization problem, which combines earlier two single‐objective optimization problems. The shape of flow channels is represented by the level set function. The pressure loss and the heat transfer performance of the channels are evaluated by the Building‐Cube Method code, which is a Cartesian‐mesh CFD solver. The proposed method resulted in an agreement with previous study in the single‐objective problems in its topology and achieved global exploration of non‐dominated solutions in the multi‐objective problems. © 2016 The Authors International Journal for Numerical Methods in Engineering Published by John Wiley & Sons Ltd 相似文献
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Patrick R. McMullen 《国际生产研究杂志》2013,51(22):6559-6582
This research addresses the problem of sequencing items for production when it is desired that the production sequences result in minimal usage rates–surrogate measures for flexibility in a JIT environment. While seeking sequences with minimal usage rates, the number of required setups for the sequences is also considered, along with feasible batch-sizing combinations. The general intent is to find minimum usage-rate sequences for each associated number of setups and total batches. This multiple objective problem is addressed via a three-dimensional efficient frontier. Because the combinatorial nature of sequencing problems typically provides an intractable search space for problems of ‘real world’ size, the search heuristics of simulated annealing and genetic algorithms are presented and used to find solutions for several problem sets from the literature. Experimentation shows that the simulated annealing approach outperforms the genetic algorithm approach in both objective function and CPU performance. 相似文献
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Q. S. Li D. K. Liu A. Y. T. Leung N. Zhang Q. Z. Luo 《International journal for numerical methods in engineering》2002,55(7):817-834
A multilevel genetic algorithm (MLGA) is proposed in this paper for solving the kind of optimization problems which are multilevel structures in nature and have features of mixed‐discrete design variables, multi‐modal and non‐continuous objective functions, etc. Firstly, the formulation of the mixed‐discrete multilevel optimization problems is presented. Secondly, the architecture and implementation of MLGA are described. Thirdly, the algorithm is applied to two multilevel optimization problems. The first one is a three‐level optimization problem in which the optimization of the number of actuators, the positions of actuators and the control parameters are considered in different levels. An actively controlled tall building subjected to strong wind action is considered to investigate the effectiveness of the proposed algorithm. The second application considers a combinatorial optimization problem in which the number and configuration of actuators are optimized simultaneously, an actively controlled building under earthquake excitations is adopted for this case study. Finally, some results and discussions about the application of the proposed algorithm are presented. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献