Application of a Parallel Adaptive Cuckoo Search Algorithm in the Rectangle Layout Problem

The meta-heuristic algorithm is a global probabilistic search algorithm for the iterative solution.It has good performance in global optimization fields such as maximization.In this paper,a new adaptive parameter strategy and a parallel communication strategy are proposed to further improve the Cuckoo Search(CS)algorithm.This strategy greatly improves the convergence speed and accuracy of the algorithm and strengthens the algorithm’s ability to jump out of the local optimal.This paper compares the optimization performance of Parallel Adaptive Cuckoo Search(PACS)with CS,Parallel Cuckoo Search(PCS),Particle Swarm Optimization(PSO),Sine Cosine Algorithm(SCA),Grey Wolf Optimizer(GWO),Whale Optimization Algorithm(WOA),Differential Evolution(DE)and Artificial Bee Colony(ABC)algorithms by using the CEC-2013 test function.The results show that PACS algorithmoutperforms other algorithms in 20 of 28 test functions.Due to the superior performance of PACS algorithm,this paper uses it to solve the problem of the rectangular layout.Experimental results show that this scheme has a significant effect,and the material utilization rate is improved from89.5%to 97.8%after optimization.

Development of Fixture Layout Optimization for Thin-Walled Parts:A Review

An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past decades.However,few papers systematically review these researches.By analyzing existing literature,this paper summarizes the process of fixture layout optimization and the methods applied.The process of optimization is made up of optimization objective setting,assembly variation/deformation modeling,and fixture layout optimization.This paper makes a review of the fixture layout for thin-walled parts according to these three steps.First,two different kinds of optimization objectives are introduced.Researchers usually consider in-plane variations or out-of-plane deformations when designing objectives.Then,modeling methods for assembly variation and deformation are divided into two categories:Mechanism-based and data-based methods.Several common methods are discussed respectively.After that,optimization algorithms are reviewed systematically.There are two kinds of optimization algorithms:Traditional nonlinear programming and heuristic algorithms.Finally,discussions on the current situation are provided.The research direction of fixture layout optimization in the future is discussed from three aspects:Objective setting,improving modeling accuracy and optimization algorithms.Also,a new research point for fixture layout optimization is discussed.This paper systematically reviews the research on fixture layout optimization for thin-walled parts,and provides a reference for future research in this field.

NOVEL APPROACH TO LOCATOR LAYOUT OPTIMIZATION BASED ON GENETIC ALGORITHM

Proper fixture design is crucial to obtain the better product quality according to the design specification during the workpiece fabrication. Locator layout planning is one of the most important tasks in the fixture design process. However, the design of a fixture relies heavily on the designerts expertise and experience up to now. Therefore, a new approach to loeator layout determination for workpieces with arbitrary complex surfaces is pro- posed for the first time. Firstly, based on the fuzzy judgment method, the proper locating reference and locator - numbers are determined with consideration of surface type, surface area and position tolerance. Secondly, the lo- cator positions are optimized by genetic algorithm（GA）. Finally, a typical example shows that the approach is su- perior to the experiential method and can improve positioning accuracy effectively.

An Improved Hybrid Genetic Algorithm for Chemical Plant Layout Optimization with Novel Non-overlapping and Toxic Gas Dispersion Constraints

New approaches for facility distribution in chemical plants are proposed including an improved non-overlapping constraint based on projection relationships of facilities and a novel toxic gas dispersion constraint. In consideration of the large number of variables in the plant layout model, our new method can significantly reduce the number of variables with their own projection relationships. Also, as toxic gas dispersion is a usual incident in a chemical plant, a simple approach to describe the gas leakage is proposed, which can clearly represent the constraints of potential emission source and sitting facilities. For solving the plant layout model, an improved genetic algorithm (GA) based on infeasible solution fix technique is proposed, which improves the globe search ability of GA. The case study and experiment show that a better layout plan can be obtained with our method, and the safety factors such as gas dispersion and minimum distances can be well handled in the solution.

Multi-Branch Cable Harness Layout Design Based on Genetic Algorithm with Probabilistic Roadmap Method

Current studies on cable harness layouts have mainly focused on cable harness route planning.However,the topological structure of a cable harness is also extremely complex,and the branch structure of the cable harness can affect the route of the cable harness layout.The topological structure design of the cable harness is a key to such a layout.In this paper,a novel multi-branch cable harness layout design method is presented,which unites the probabilistic roadmap method(PRM)and the genetic algorithm.First,the engineering constraints of the cable harness layout are presented.An obstacle-based PRM used to construct non-interference and near to the surface roadmap is then described.In addition,a new genetic algorithm is proposed,and the algorithm structure of which is redesigned.In addition,the operation probability formula related to fitness is proposed to promote the efficiency of the branch structure design of the cable harness.A prototype system of a cable harness layout design was developed based on the method described in this study,and the method is applied to two scenarios to verify that a quality cable harness layout can be efficiently obtained using the proposed method.In summary,the cable harness layout design method described in this study can be used to quickly design a reasonable topological structure of a cable harness and to search for the corresponding routes of such a harness.

Application of Genetic Algorithm in the Layout of Fixture Components

Automation in the layout of fixture components is important to achieve efficiency and flexibility in computer aided fixture design. Based on basic genetic algorithm and particulars of different fixture components, a method of layout space division is presented. Such techniques as suitable crossover rate, mutation rate and selection arithmetic element are adopted in the genetic operation. The results show that genetic algorithm can effectively be applied in the automatic layout of fixture components.

Hybrid Genetic Algorithm and Variable Neighborhood Search for Dynamic Facility Layout Problem

This paper presents a novel hybrid metaheuristic GA-VNS matching genetic algorithm (GA) and variable neighborhood search (VNS) to the dynamic facility layout problem (DFLP). The DFLP is a well-known NP hard problem which aims at assigning a set of facilities to a set of locations over a time planning horizon so that the total cost including material handling cost and re-arrangement cost is minimized. The proposed hybrid approach in this paper elegantly integrates the exploitation ability of VNS and exploration ability of GA. To examine the performance of the proposed hybrid approach, a set of instance problems have been used from the literature. As demonstrated in the results, the GA-VNS is mighty of attaining high quality solution. Compared with some state-of-the-art algorithms, our proposed hybrid approach is competitive.

Integrated optimal method for cell formation and layout problems based on hybrid SA algorithm with fuzzy simulation

To adapt to the complex and changeable market environment,the cell formation problems(CFPs) and the cell layout problems(CLPs) with fuzzy demands were optimized simultaneously. Firstly,CFPs and CLPs were described formally. To deal with the uncertainty fuzzy parameters brought,a chance constraint was introduced. A mathematical model was established with an objective function of minimizing intra-cell and inter-cell material handling cost. As the chance constraint of this problem could not be converted into its crisp equivalent,a hybrid simulated annealing(HSA) based on fuzzy simulation was put forward. Finally,simulation experiments were conducted under different confidence levels. Results indicated that the proposed hybrid algorithm was feasible and effective.

An Algorithm for Solving Generalized Single Row Facility Layout Problem

Layout design problem is to determine a suitable arrangement for the departments so that the total costs associated with the flow among departments become least. Single Row Facility Layout Problem, SRFLP, is one of the layout problems that have many practical applications. This problem and its specific scenarios are often used to model many of the raised issues in the field of facility location. SRFLP is an arrangement of n departments with a specified length in a straight line so that the sum of the weighted distances between the pairs of departments is minimized. This problem is NP-hard. In this paper, first, a lower bound for a special case of SRFLP is presented. Then, a general case of SRFLP is presented in which some new and real assumptions are added to generate more practical model. Then a lower bound, as well as an algorithm, is proposed for solving the model. Experimental results on some instances in literature show the efficiency of our algorithm.

增强多层网络心理地图保持效果的力引导布局算法

为了增强多层网络可视化中网络布局的心理地图保持效果,减轻读者在跨层分析任务中的认知负担,提出一种应用于切片式多层网络可视化的力引导布局算法.首先计算节点副本间的单向吸引系数;然后根据单向吸引系数和各节点副本的当前位置计算各节点副本的理想位置及距离差;最后结合距离差损失项、KK算法能量函数和节点副本间距损失项构建损失函数并优化得到布局方案.通过在10个公开数据集,包括7个社交网络数据集、3个遗传网络数据集上,与同类型算法对比在心理地图保持指标,即节点移动总距离上的表现的结果表明,所提算法能够显著增强多层网络布局的心理地图保持效果.

综合公园空间布局优化的模型构建及实证分析

综合公园作为重要且稀缺的城市公共资源,其合理布局对城市存量更新背景下优化公园体系、增进民生福祉具有重要意义。布局优化模型常用于解决公共服务设施布局问题,新重力P中值模型是一种综合多目标导向、设施供需匹配关系和复杂约束条件的布局优化方法。在辨析新重力P中值模型的基础上,综合考虑供给主体差异和模型求解难度,构建出面向城市综合公园布局优化的改进新重力P中值模型,主要修正内容如下:(1)通过细化供给主体,改良规模分配规则,改进新重力P中值模型未考虑现有公园和新建公园服务供给差异性的局限;(2)引入遗传算法寻优,解决非线性、多约束的复杂设施布局问题,实现模型求解以促进模型在公园实际规划中的推广应用。以苏州市中心城区为例,以多源数据为支撑,将研究尺度下沉至居住区尺度,实证结果表明模型优化后居民至邻近综合公园最大出行成本、平均出行成本和可达性基尼系数等指标均有改善,综合公园空间布局更为合理。研究结果可为综合公园布局规划提供有效决策工具,为公园绿地的精准化布局提供参考。

可重构低熵智能车间布局建模与优化

针对智能车间布局,采用单元布局的方式分别对单元间布局和单元内布局进行建模,设计涵盖物料搬运成本、时间损失成本、单元重构成本、设备成本、车间面积利用率和布局柔性等面向低熵化车间布局的多目标函数,给出包括边界约束、间距约束和固定位置约束等符合车间实际情况的定量约束条件。针对车间布局模型多变量、多约束和非线性的特点,设计一种基于精英策略和自适应交叉、变异算子的双层遗传元胞算法进行求解。通过典型企业作业车间布局改造实例分析,验证模型和算法的可行性和有效性。

基于低碳物流的危化品仓库堆垛布局优化研究

为保证危化品仓库安全的同时有效减少碳排放并提升经济效益,建立危险指数最小、物料搬运量最小和碳排放成本最小的危化品仓库堆垛布局多目标优化模型,采用改进的粒子群-禁忌搜索混合算法对模型进行求解。该算法在传统粒子群算法的基础上加入多点变异操作,并在粒子群算法得出解的基础上加入禁忌搜索算法,提高算法跳出局部最优解的能力。研究结果表明:利用本文建立的多目标优化模型及改进算法,危险指数、物料搬运量和碳排放成本均有所下降,解集质量较高,从而在保证危化品安全的情况下,有效降低物料搬运量及碳排放成本。研究结果可为危化品企业对仓库内部碳排放量的影响因素和数值计算以及危化品仓库安全性的界定提供参考与借鉴。

基于改进MH算法的室内空间自动布局

为了生成文博展厅、城市阅读空间、商场等具备公共服务职能的空间布局,提出了一种面向室内空间的自动布局方法。该方法首先针对多种布局的表达需求,将布局信息记录在层次化图结构中;再按照图结构填充适当的布局对象作为初始状态;利用能量函数和移动策略,引入改进的MH(Metropolis-Hastings)算法进行优化,生成合适的布局方案。选取多种类型的应用场景进行测试,结果证明了该方法的有效性。根据公共空间设计原则,提出评价指标比较各类方法性能。该方法在布置效率和运算效率方面具有优势,可应用于多种类型的公共空间布局设计。

舰船管路布置PG-MACO优化方法

针对舰船管路设计效率低下的问题提出一种管路布置优化方法.综合考虑安全性、经济性、协调性和可操作性等工程背景建立优化数学模型,改进蚁群算法在处理混合管路布置工况下的缺陷,提出优化可行解搜索的空间状态转移策略,提升信息素启发效果并加速算法收敛的信息素扩散机制,面向混合管路布置工况设计多蚁群协同进化机制.基于二次开发技术实现本方法在第三方设计软件上的应用,采用核级一回路管道布置工程案例进行验证.结果表明信息素高斯扩散多蚁群优化(PG-MACO)算法的性能和布置效果优于传统蚁群算法,寻路效率提升58.38%,收敛代数缩短43.24%,布置结果中管路长度缩短33.88%,管路折弯次数减少41.67%,验证了本方法的有效性和工程实用性.

基于最优觅食算法的增材制造中多种类零件分批排样研究

增材制造中多种类零件分批排样存在打印时间成本高和工作台空间利用率低等问题,且需考虑零件高度的影响。分批排样问题包括零件在工作台上放置策略和成型批次分配两个子问题。放置策略涉及成型方向选择、零件碰撞检测和定位策略。基于建立的成型方向准则,利用多边形表示零件投影轮廓,提出基于临界多边形的改进移动碰撞法以确定3种不同形态多边形零件的免碰撞排放范围,提出新的左下定位策略放置零件,新定位策略融合了改进的建设性方法和契合度;提出单机台面积占用最大化策略实现零件成型批次分配。基于上述研究,提出基于最优觅食算法的分批排样算法,算法采用双重编码表达零件放置顺序和旋转角度,以最小化完工时间为目标实现优化分批排样。以案例库零件为对象,与3种对比算法比较,表明所提方法的方案能有效提高增材制造的空间利用率和缩短完工时间。

基于BIM的PC构件排样优化设计

针对PC构件排样与上游装配式建筑设计模型的协同效用问题,进行了基于BIM的PC构件排样优化设计研究。分析了装配式BIM中PC构件的组成元素,完成PC构件信息的提取;结合改进蚁群算法与动态剩余矩形算法对PC构件排样进行优化,采用遗传变异策略与路径选择机制改进算法后期易陷入局部最优的不足,经过多次优化迭代得出最优排样。某PC构件企业的生产排样实例验证了基于BIM的PC构件排样优化方案可实现上游装配式建筑设计模型与PC构件排样的协同效用,提高了排样效率。

地下隐蔽工程地源热泵地埋管管群优化研究

地下建筑地源热泵系统向地下释放的热量常大于所提取的热量,容易造成地埋管区域的热量累积,影响其正常使用。因此,提高地埋管换热器效率,减弱冷热量失衡影响,是地下隐蔽工程应用地源热泵系统亟需解决的问题。文章基于换热器温差场均匀性原则,采用全局优化遗传算法,优化了地埋管换热器管群布置。结果表明:与传统等间距方案相比,优化布置后,16、25个钻孔方案的平均无因次温变热阻分别降低了13.8%和53.3%,平均换热效率分别提高了3.76%和5.74%,即钻孔数量越多,换热效率提升越明显。

基于SLP的物流无人机垂直起降场功能区布局研究

物流无人机垂直起降场是无人机物流系统重要基础设施,其功能区布局和货运作业流程影响货物收发安全和效率。根据无人机物流配送运行要求,首先对无人机垂直起降场的功能区进行划分,然后以搬运成本最小和功能区间综合关系值最大构建功能区布局数学模型,并确定约束条件;通过应用系统布置设计(SLP)方法,结合算例分析功能区间的综合关系,采用遗传算法得出最优功能区布局。研究发现,该方法得出的最优方案空间利用率高、经济成本低,可作为物流无人机垂直起降场建设的参考。

二阶聚类和蜂群算法的城市生态景观用地空间布局优化方法

传统城市生态景观用地空间布局方法受到城市建设功能性、土地使用性质等多因素限制,在生态景观用地空间布局过程中存在局部偏差,所得布局结果的合理性与设计预期布局之间存在一定差距,在一定程度上影响力城市布局进度及其整体布局效果。为了彻底解决这一问题,结合城市生态景观用地空间属性,引入二阶聚类、蜂群算法两种优化方案共同对其布局进行优化。首先,城市生态景观用地空间布局优化目标函数确认;然后,蜂群算法引入及参量定义更新;最后,蜂群优化布局策略的二阶聚类优化输出;通过仿真性能对比结果,能够说明提出优化方法局部提升布局合理性,降低多因素扰动对布局结果的影响,改善布局结果精准度的能力,满足方法设计预期。