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1.
通过总结混流装配线排序问题,提出了一种新的装配线排序模型.根据装配车型的关键件不同,引入车型相似度的概念,应用遗传算法解决以最大化相似度总和为目标的混流装配线优化排序问题.经实践中应用,关键件装配更换次数减少了70%.  相似文献   

2.
混流装配线上的产品投产排序是影响装配线生产效率的重要因素.建立以最小化装配线总闲置—超载成本为优化目标的装配线排序模型,采用粒子群算法来解决混流装配线的投产排序问题.考虑到基本粒子群算法易陷入局部最优解的问题,引入免疫算法思想对其进行改进,根据抗体亲和性与浓度值的计算,及时进行粒子的替换以维持种群的多样性,防止粒子过早...  相似文献   

3.
基于连续函数优化的禁忌搜索算法   总被引:1,自引:0,他引:1  
提出了一种连续禁忌搜索算法,用于求解连续函数优化问题.邻域规则及禁忌规则是禁忌搜索算法的核心,针对连续函数解空间的连续性,提出了一种邻域分割法来进行邻域搜索,并对禁忌规则进行了设计.通过经典函数测试可以看出,禁忌搜索算法在连续函数优化问题中显示出很强的"爬山"能力,优化结果与实际最优值非常接近,是一种有效的全局优化算法.  相似文献   

4.
面向多处理器SoC设计的低功耗软硬件划分   总被引:1,自引:0,他引:1  
提出了解决多处理器SoC的低功耗软硬件划分问题的方法--基于神经网络的禁忌搜索算法.其基本思想是:真实的生物神经元具有抑制重复激活的阻尼特性,这与禁忌搜索对重复搜索加以限制相类似,因此设计具有阻尼特性的神经网络实现禁忌搜索算法,受阻尼特性抑制的神经元对应禁忌活动.由于神经网络复杂的动态特性和禁忌搜索优秀的全局搜索能力,该算法能够有效地跳出局部最优解.对真实任务图的实验表明,与遗传算法相比,该算法不但具有搜索速度上的优势,而且所得到的绝大部分软硬件划分方案有更低的系统功耗.  相似文献   

5.
针对混流装配线按工作日历调度过程中,组批生产导致订单准时交付率差、加班时间长,以及缺料等干扰因素导致完工周期延长等问题,以零部件配套、按工作日历组批为约束,最小化完工周期、提前/拖期时间以及加班时间为多目标,建立工件排序数学优化模型。验证以完工周期最短为目标的流水线工件最优排序亦具有V型特征。提出空间蚁群权重设计方法,将蚂蚁沿不同的权重向量寻优,提高算法的全局搜索能力;并根据当前Pareto解在各权重子空间的分布情况动态调整各子空间的蚂蚁数量,避免陷入局部最优。通过与文献算法对比,验证空间蚁群算法具有良好的优化性能,并通过实例验证了排序方法的有效性。  相似文献   

6.
针对零部件供应不能实现JIT的混流装配线排序问题,提出在SPS物料配送模式下,以提高零部件配送质量为目的,分析拣选环节筐车排列顺序对零件拣选错配和漏配的影响,从两方面探讨通过安排筐车排列顺序以最小化拣选错配和漏配率;同时在总装环节,追求零部件消耗速率均衡化.从而建立同时考虑总装和零部件配送两阶段优化的混流装配线排序模型.结合排序案例,证明该排序模型能在平准化零部件消耗的同时提高配送质量.  相似文献   

7.
本文研究了考虑工人装配水平差异、不同工位之间可以流动分配的装配线工人优化调度,在确定混流装配线的排序后,装配工人在其最擅长的工位工作,在完成本工位的工作后参与其他工位的装配工作,定义相关的优化因素变量和约束条件,建立了考虑工人工位效率差异且可流动分配的混流装配线工人优化数学模型。采用削峰填谷算法和多种群移民算法进行工人的调整和均衡优化,利用一个三层神经网络对削峰填谷的工位进行评估选择,得到工人的最优分配方案,最后通过Matlab对举例进行了验证。算例优化后,减少了2名装配工人,并提高了装配线的平衡率。  相似文献   

8.
为提高混流产品拆卸效率,针对固定工作站数量约束、位置约束、优先关系约束,考虑任务操作完成时间的不确定性,建立了以最小化循环时间(Cycle Time,CT)和最小化工作站平均空闲时间为目标的混流U型拆卸线平衡排序问题的数学模型。结合混流拆卸线的具体特点,提出了一种改进的并行邻域搜索算法(Improved Parallel Neighborhood Search,IPNS),该算法定义两类不同的邻域结构,采用动态搜索策略,通过独立搜索以及直接交换邻域的方式以最大限度寻找最优解。最后,通过多个算例验证了算法的有效性。  相似文献   

9.
为有效解决带有顺序相关调整时间的双边装配线平衡问题,提出了一种简单高效的变邻域搜索算法。该算法通过将优先关系约束融入到交换、插入、交叉、变异等算子中,分别得到4个不同的邻域结构来保证搜索过程中解的可行性,避免过多重复邻域解的生成。4个邻域结构的搜索空间依次变大,以增强算法搜索能力。同时,结合装配线的特点,提出基于作业序列的编码和解码方式,在解码过程中,优先选择空闲时间较多的边,引入启发式目标加快算法收敛。分配结束后,对装配线末端的工作站组进行局部调整。通过将该算法先后用于求解无/有顺序相关调整时间的双边装配线平衡第一类问题,并与已有的算法进行对比,验证了所提的变邻域搜索算法的优越性和有效性。  相似文献   

10.
从数学角度分析,配电网无功优化是一个非线性、多变量、多约束的混合规划问题。粒子群优化搜索算法被广泛应用于求解配电网无功优化问题。由于粒子群算法粒子群在进化过程易趋向同一化,失去多样性,从而使算法陷入局部最优解。本文在分析配电网无功优化的特性基础上,提出一种改进的紧融合禁忌搜索-粒子群算法用于配电网无功优化问题的求解。通过将禁忌搜索功能融合到粒子历史最优解和全局最优解寻优过程中,避免了粒子群算法寻优过程中出现的局部最优问题,从而提高粒子群算法的全局搜索能力。通过IEEE14节点系统的仿真计算结果表明,改进的算法能取得良好的效果。  相似文献   

11.
Mixed-model assembly lines are widely used to improve the flexibility to adapt to the changes in market demand, and U-lines have become popular in recent years as an important component of just-in-time production systems. As a consequence of adaptation of just-in-time production principles into the manufacturing environment, mixed-model production is performed on U-lines. This type of a production line is called a mixed-model U-line. In mixed-model U-lines, there are two interrelated problems called line balancing and model sequencing. In real life applications, especially in manual assembly lines, the tasks may have varying execution times defined as a probability distribution. In this paper, the mixed-model U-line balancing and sequencing problem with stochastic task times is considered. For this purpose, a genetic algorithm is developed to solve the problem. To assess the effectiveness of the proposed algorithm, a computational study is conducted for both deterministic and stochastic versions of the problem.  相似文献   

12.
为了推动鱼骨型仓库在实际场景下的应用,针对鱼骨型仓库布局下的拣货路径优化问题,构建待拣货点距离计算模型和以有载重、容积限制的多车拣货距离最短为总目标的拣选路径优化模型。考虑遗传算法(GA)全局搜索能力强、粒子群算法(GAPSO)收敛速度快以及蚁群算法(ACO)较强的局部寻优能力,提出一种解决拣选路径优化模型的混合算法(GA-PSO-ACO)。通过不同订单规模的仿真实验,得出该混合算法在适应度值、迭代次数、收敛速度等方面均优于GA算法和GAPSO算法,且在订单规模较大时,平均适应度值约降低8%,有效缩短了总拣选距离,验证了混合算法在解决鱼骨型仓库布局下的拣货路径问题的先进性和有效性,为解决此类仓库内部的拣货路径问题提供新的解决方法和思路。  相似文献   

13.
Implementation of mixed-model U-shaped assembly lines (MMUL) is emerging and thriving in modern manufacturing systems owing to adaptation to changes in market demand and application of just-in-time production principles. In this study, the line balancing and model sequencing (MS) problems in MMUL are considered simultaneously, which results in the NP-hard mixed-model U-line balancing and sequencing (MMUL/BS) problem. A colonial competitive algorithm (CCA) is developed and modified to solve the MMUL/BS problem. The modified CCA (MCCA) improves performance of original CCA by introducing a third type of country, independent country, to the population of countries maintained by CCA. Implementation details of the proposed CCA and MCCA are elaborated using an illustrative example. Performance of the proposed algorithms is tested on a set of test-bed problems and compared with that of existing algorithms such as co-evolutionary algorithm, endosymbiotic evolutionary algorithm, simulated annealing, and genetic algorithm. Computational results and comparisons show that the proposed algorithms can improve the results obtained by existing algorithms developed for MMUL/BS.  相似文献   

14.
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   

15.
Growing interests from customers in customised products and increasing competitions among peers necessitate companies to configure their manufacturing systems more effectively than ever before. We propose a new assembly line system configuration for companies that need intelligent solutions to satisfy customised demands on time with existing resources. A mixed-model parallel two-sided assembly line system is introduced based on the parallel two-sided assembly line system previously proposed in the literature. The mixed-model parallel two-sided assembly line balancing problem is illustrated with examples from the perspective of simultaneous balancing and sequencing. An agent-based ant colony optimisation algorithm is proposed to solve the problem. This algorithm is the first attempt in the literature to solve an assembly line balancing problem with an agent-based ant colony optimisation approach. The algorithm is illustrated with an example and its operational procedures and principles are explained and discussed.  相似文献   

16.
A novel hybrid genetic algorithm (HGA) is proposed to solve the branch-cut phase unwrapping problem. It employs both local and global search methods. The local search is implemented by using the nearest-neighbor method, whereas the global search is performed by using the genetic algorithm. The branch-cut phase unwrapping problem [a nondeterministic polynomial (NP-hard) problem] is implemented in a similar way to the traveling-salesman problem, a very-well-known combinational optimization problem with profound research and applications. The performance of the proposed algorithm was tested on both simulated and real wrapped phase maps. The HGA is found to be robust and fast compared with three well-known branch-cut phase unwrapping algorithms.  相似文献   

17.
18.
混合模拟植物生长算法在包装件配送中的应用   总被引:1,自引:1,他引:0  
樊贵香 《包装工程》2016,37(13):43-49
目的针对改进模拟植物生长算法(IPGSA)容易陷入局部最优解及其算法运行时间较长,提出混合模拟植物生长算法(HPGSA)来求解带时间窗车辆调度问题(VSPTW)。方法在IPGSA基础上,提出求解包装件物流配送中VSPTW的混合模拟植物生长算法(HPGSA)。改进IPGSA初始调度方案的构造方式,设计求解VSPTW的C-W算法用于构造HPGSA的初始调度方案;改进IPGSA的邻域搜索算子,选择插入搜索算子和互换搜索算子对HPGSA进行邻域搜索;对18个不同规模的Solomon算例进行仿真测试。结果相对于其他智能算法,HPGSA具有更好的求解性能,能够保证VSPTW对求解算法的要求。结论 HPGSA的全局优化能力、稳定性和运行速度均优于IPGSA、遗传算法、蚁群算法和禁忌搜索算法。  相似文献   

19.
包装物回收物流中的车辆路径优化问题   总被引:2,自引:2,他引:0  
张异 《包装工程》2017,38(17):233-238
目的提高遗传算法(GA)求解包装物回收车辆路径优化问题的性能。方法通过对传统GA算法的改进,提出混合蜂群遗传算法(HBGA)。首先改进传统GA算法的初始种群生成方式,设计初始种群混合生成算子;其次,提出最大保留交叉算子,对优秀子路径进行保护;然后,在上述改进的基础上引入蜜蜂进化机制,用以保证种群多样性和优秀个体特征信息的利用程度;最后,对标准算例集进行仿真测试。结果与传统GA算法相比,HBGA算法在全局寻优能力、算法稳定性和运行速度方面均有所改善。HBGA算法的全局寻优能力和算法稳定性均优于粒子群算法(PSO)、蚁群算法(ACO)和禁忌搜索算法(TS),但运行速度稍慢于TS算法。结论对传统GA算法的改进是合理的,且HBGA算法整体求解性能优于PSO算法、ACO算法和TS算法。  相似文献   

20.
The beam-type placement machine is capable of picking up multiple components simultaneously from the feeders in printed circuit board (PCB) assembly. Simultaneous pickup occurs only if the heads in the beam are aligned with the feeders and the nozzle-types on these heads match with the component-types on the feeders. In order to minimise the assembly cycle time, the optimisation problem is decomposed into two sub-problems, the pickup combination and sequencing problem, and the placement cluster and sequencing problem. These two sub-problems are simultaneously solved by the proposed hybrid genetic algorithm (HGA). The pickup combination and sequencing problem is similar to the popular multi-compartment vehicle routing problem (MCVRP); a genetic algorithm (GA) for the MCVRP is therefore modified and applied to solving the pickup combination and sequencing problem. A greedy heuristic algorithm is used to solve the placement cluster and sequencing problem. The numerical experiments reveal that the HGA outperforms the algorithms proposed by previous papers.  相似文献   

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