一种多目标不等面积设施布局问题的启发式算法

多目标不等面积设施布局问题（UA-FLP）是将一些不等面积设施放置在车间内进行布局,要求优化多个目标并满足一定的限制条件。以物料搬运成本最小和非物流关系强度最大来建立生产车间的多目标优化模型,并提出一种启发式算法进行求解。算法采用启发式布局更新策略更新构型,通过结合基于自适应步长梯度法的局部搜索机制和启发式设施变形策略来处理设施之间的干涉性约束。为了得到问题的Pareto最优解集,提出了基于Pareto优化的局部搜索和基于小生境技术的全局优化方法。通过两个典型算例对算法性能进行测试,实验结果表明,所提出的启发式算法是求解多目标UA-FLP的有效方法。     

基于Wang-Landau抽样的带静不平衡约束的简化卫星舱布局方法

以简化卫星舱承载板上三维布局设计问题为背景,研究一类带静不平衡约束的圆柱体和长方体混合待布物布局问题。针对该三维布局问题,将已成功应用于统计物理学和蛋白质结构预测的Wang-Landau抽样算法引入布局问题中。Wang- Landau抽样算法通过在复杂布局空间中进行有效抽样来得到一个平坦的能量直方图,从而精确估计布局系统的状态密度。通过将Wang- Landau抽样算法与带加速策略的最速下降法、质心平移策略相结合,提出了改进的Wang-Landau抽样算法。对文献中两个算例进行了实算,计算结果表明,改进的Wang-Landau抽样算法的收敛速度和解的质量相比文献中其它算法均有较大的提高。     

一种求解多维0-1背包问题的拟人算法

在项目决策与规划,资源分配,货物装载等工作中,提出了多维0-1背包问题,对这一问题,国内外学者提出了诸如模拟退火算法,遗传算法,蚁群算法及其它一些启发式算法等求解算法。该文提出了一种新的启发式求解算法。该算法使用了两个主要的思想策略,即依据物品单位容积价值的高低选择物品并对其进行标记的策略和拟人跳坑策略。用本文提出的算法,对55个测试算例进行了实算测试,得到了其中54个算例的最优解。测试结果表明,用该文提出的拟人算法求解多维0-1背包问题,计算结果的优度高,计算时间短,是求解此问题的有效算法。     

求解二维正交矩形布局问题的动态填空启发式算法

为更高效解决二维正交矩形布局问题,建立该问题的数学模型,改进BL算法规则;为寻找布局过程中的空余平面,建立了新颖的图形矩阵化理论。最后提出一种动态填空（DFB）启发式算法,制定了四条动态调整机制,结合遗传算法对该问题进行求解。大量算例测试显示：DFB算法可达到100%的平面利用率,极大提高了BL算法的效率,并且可以适用于大规模布局问题。     

带静不平衡约束的矩形装填问题的启发式算法

卫星舱布局问题不仅是一个复杂的耦合系统设计问题,也是一个特殊的优化问题,具有NP难度性。解决这类问题最大的挑战在于需要优化的目标函数具有大量的被高能势垒分隔开的局部极小值点。Wang-Landau（WL）抽样算法是一种改进的蒙特卡罗方法,已经被成功地运用蛋白质结构预测等优化问题。本文以卫星舱布局优化问题为背景,首次将WL抽样算法引入矩形装填问题的求解。针对矩形装填物的特点,提出了启发式格局更新策略,以引导抽样算法在解空间中进行有效行走。为了加速搜索全局最优解,每次蒙特卡罗扫描生成新的布局时,便执行梯度法进行局部搜索。通过将局部搜索机制、启发式格局更新策略与WL抽样算法相结合,提出了一种用于解决带静不平衡约束的任意矩形装填问题的启发式布局算法。在布局优化过程中,通过在挤压弹性势能的基础上增加静不平衡量惩罚项并采用质心平移的方法,使布局系统的静不平衡量达到约束要求。另外,为了改进算法的搜索效率,提出了改进的有限圆族法用于装填物之间的干涉性判断和干涉量计算。通过对文献中两组共10个有代表性的算例进行实算,计算结果表明,所提出的装填算法是一种求解带静不平衡性能约束的任意矩形装填问题的有效算法。     

一种解决矩形布局问题的启发式快速算法

针对二维矩形Packing问题,提出了一种沿阶梯线轮廓进行布局矩形的启发式算法.该算法基于"阶梯式堆码"的启发式规则,能够快速地对矩形块进行紧靠布局.为避免算法陷入局部最优,算法采用随机回溯策略在选择矩形和阶位上扩大搜索范围.结果表明,算法对于浪费面积为零的矩形全Packing问题,能够在极短的时间内找到最优解,同时它也可以很好地求解非零浪费问题.采用国际公认的两个算例进行测试,证明文中算法是非常高效的.     

一种求解圆形Packing问题的模拟退火算法?

为求解矩形区域内的圆形Packing问题,提出一种启发式模拟退火算法。寻求多个圆在一个矩形区域内的优良布局,使这些圆两两互不嵌入地放置。算法从任一初始构形出发,采用模拟退火(SA)算法进行全局寻优,在SA执行过程中,应用基于自适应步长的梯度法进行局部搜索,同时介绍一些启发式策略。对2组共20个算例进行实算测试,计算结果证明了该算法的有效性。     

正三角形容器内等圆Packing问题的启发式算法

等圆Packing问题研究如何将n个单位半径的圆形物体互不嵌入地置入一个边长尽量小的正三角形容器内,作为一类经典的NP难度问题,其有着重要的理论价值和广泛的应用背景.模拟退火算法是一种随机的全局寻优算法,通过将启发式格局更新策略与基于梯度法的局部搜索策略融入模拟退火算法,并与二分搜索相结合,提出一种求解正三角形容器内等圆Packing问题的启发式算法.该算法将启发式格局更新策略用来产生新格局和跳坑,用梯度法搜索新产生格局附近能量更低的格局,并用二分搜索得到正三角形容器的最小边长.对41个算例进行测试的实验结果表明,文中算法改进了其中38个实例的目前最优结果,是求解正三角形容器内等圆Packing问题的一种有效算法.     

基于改进NSGA-Ⅱ算法的多目标设施动态布局问题研究

为解决高效的车间动态设施布局问题,以重布局费用、非物流关系和面积利用率为目标,对NSGA-Ⅱ算法进行了优化,将随机变异操作与最近和最远法的非支配解选择结合,对NSGA-Ⅱ算法进行了改进并对其进行求解。通过经典算例的模型求解测试,验证了该方法的可行性和有效性。     

基于模拟退火算法的布局问题研究

在传统模拟退火算法的基础上,对布局问题的优化算法进行了研究,采用回火策略,改进一般模拟退火算法寻优的效果;结合布局问题的具体特点,采用Sequence Pair来描述布局问题的解结构,综合构成了一种新的求解布局问题的模拟退火算法.通过算例验证,该算法优于传统优化算法和普通启发式搜索算法,并且对增量布局也能够取得较好的效果.     

Applying multi-objective ant colony optimization algorithm for solving the unequal area facility layout problems

The unequal area facility layout problem (UA-FLP) which deals with the layout of departments in a facility comprises of a class of extremely difficult and widely applicable multi-objective optimization problems with constraints arising in diverse areas and meeting the requirements for real-world applications. Based on the heuristic strategy, the problem is first converted into an unconstrained optimization problem. Then, we use a modified version of the multi-objective ant colony optimization (MOACO) algorithm which is a heuristic global optimization algorithm and has shown promising performances in solving many optimization problems to solve the multi-objective UA-FLP. In the modified MOACO algorithm, the ACO with heuristic layout updating strategy which is proposed to update the layouts and add the diversity of solutions is a discrete ACO algorithm, with a difference from general ACO algorithms for discrete domains which perform an incremental construction of solutions but the ACO in this paper does not. We propose a novel pheromone update method and combine the Pareto optimization based on the local pheromone communication and the global search based on the niche technology to obtain Pareto-optimal solutions of the problem. In addition, the combination of the local search based on the adaptive gradient method and the heuristic department deformation strategy is applied to deal with the non-overlapping constraint between departments so as to obtain feasible solutions. Ten benchmark instances from the literature are tested. The experimental results show that the proposed MOACO algorithm is an effective method for solving the UA-FLP.     

Multi-objective layout optimization of a satellite module using the Wang-Landau sampling method with local search

The layout design of satellite modules is considered to be NP-hard. It is not only a complex coupled system design problem but also a special multi-objective optimization problem. The greatest challenge in solving this problem is that the function to be optimized is characterized by a multitude of local minima separated by high-energy barriers. The Wang-Landau (WL) sampling method, which is an improved Monte Carlo method, has been successfully applied to solve many optimization problems. In this paper we use the WL sampling method to optimize the layout of a satellite module. To accelerate the search for a global optimal layout, local search (LS) based on the gradient method is executed once the Monte-Carlo sweep produces a new layout. By combining the WL sampling algorithm, the LS method, and heuristic layout update strategies, a hybrid method called WL-LS is proposed to obtain a final layout scheme. Furthermore, to improve significantly the efficiency of the algorithm, we propose an accurate and fast computational method for the overlapping depth between two objects (such as two rectangular objects, two circular objects, or a rectangular object and a circular object) embedding each other. The rectangular objects are placed orthogonally. We test two instances using first 51 and then 53 objects. For both instances, the proposed WL-LS algorithm outperforms methods in the literature. Numerical results show that the WL-LS algorithm is an effective method for layout optimization of satellite modules.     

Facility layout by collision detection and force exertion heuristics

Facility layout problem (FLP) considers the optimization of layout costs, primarily on the account of material handling costs. FLP can be solved via mathematical modelling, heuristic or metaheuristic approaches. This paper presents a novel heuristic approach for solving the unequal area FLP. Here, facilities are randomly generated points that exert forces on each other based on a relation matrix. In this setup, every point is a centroid of the respective facility shape and two heuristic methods are used to detect and consequently remove the collisions where the heuristic parameters influence the speed and quality of the final results. Furthermore, a graphic user interface (GUI) is designed to monitor performance of the proposed heuristic algorithm and modify its parameters while running if required. Finally, layout in higher dimensional space, facility rotation and future possible extensions are discussed.     

A heuristic procedure for the integrated facility layout design and flow assignment problem

We present an efficient iterative heuristic procedure for solving the integrated layout design and product flow assignment problem. The layout design decisions involve planar location of unequal-area machines with duplicates. The product flows are assigned to machines according to the product processing routes. The integrated decision problem is a nonlinear mixed integer model which cannot be efficiently solved using classical methods for large problems. We propose a novel integrated heuristic procedure based on the alternating heuristic, a perturbation algorithm and sequential location heuristic. Since the alternating heuristic between facility layout design and product-machine assignment sub-problems terminates with local optima, we developed a perturbation algorithm based on assignment decisions. The results of an experimental study show that proposed procedure is both efficient and effective in identifying quality solutions for small to very large-sized problems.     

带静不平衡约束的正交矩形布局问题的启发式模拟退火算法*

以卫星舱布局为背景,研究一类带静不平衡约束的正交矩形布局问题.借鉴拟物策略,定义矩形与矩形、矩形与圆形容器之间的嵌入度计算公式,将该问题转变为无约束的优化问题.通过将启发式格局更新策略、基于梯度法的局部搜索机制与具有全局优化功能的模拟退火算法相结合,提出一种求解带静不平衡约束的正交矩形布局问题的启发式模拟退火算法.算法中的启发式格局更新策略产生新格局和跳坑,梯度法搜索新格局附近能量更低的格局.另外,在布局优化过程中,通过在挤压弹性势能的基础上增加静不平衡量惩罚项,并采用质心平移的方法,使布局系统的静不平衡量达到约束要求.实验表明,文中算法是一种解决带静不平衡约束的正交矩形布局问题的有效算法.     

Simulated annealing heuristics for the dynamic facility layout problem

In today's economy, manufacturing plants must be able to operate efficiently and respond quickly to changes in product mix and demand. Therefore, this paper considers the problem of arranging and rearranging (when there are changes between the flows of materials between departments) manufacturing facilities such that the sum of the material handling and rearrangement costs is minimized. This problem is known as the dynamic facility layout problem (DFLP). In this paper, two simulated annealing (SA) heuristics are developed for the DFLP. The first SA heuristic (SA I) is a direct adaptation of SA to the DFLP. The second SA heuristic (SA II) is the same as SA I with a look-ahead/look-back strategy added. To test the performance of the heuristics, a data set taken from the literature is used in the analysis. The results obtained show that the proposed heuristics are very effective for the dynamic facility layout problem.     

考虑动态平衡装卸的点对点取送货车辆路径优化

针对点对点取送货车辆路径优化问题,引入动态平衡、后进先出、三维装载等约束,以总路径最短为优化目标,构建多车多客户应用场景下的动态平衡装卸点对点取送货车辆路径优化模型;基于研究问题的特征,采用启发式插入法确定路径初始方案,设计节点交换和重新定位算子,构造路径邻域方案,并将动态平衡装卸纳入路径迭代过程,运用多重指标定序策略和三分空间策略,设计客户动态平衡装卸检算算法,并提出基于禁忌搜索的点对点取送货车辆路径优化算法,制订多车多客户取送货车辆路径方案的同时编制动态平衡装载方案。最后,通过标准算例验证方法的有效性,计算表明：所提方法能高效解决带动态平衡约束的点对点取送货车辆路径优化问题;在多车多客户应用场景下具有更强的寻优能力,求解效率更高。