A tabu search based approach for graph layout

This paper describes an automated tabu search based method for drawing general graph layouts with straight lines. To our knowledge, this is the first time tabu methods have been applied to graph drawing. We formulated the task as a multi-criteria optimization problem with a number of metrics which are used in a weighted fitness function to measure the aesthetic quality of the graph layout. The main goal of this work is to speed up the graph layout process without sacrificing layout quality. To achieve this, we use a tabu search based method that goes through a predefined number of iterations to minimize the value of the fitness function. Tabu search always chooses the best solution in the neighbourhood. This may lead to cycling, so a tabu list is used to store moves that are not permitted, meaning that the algorithm does not choose previous solutions for a set period of time. We evaluate the method according to the time spent to draw a graph and the quality of the drawn graphs. We give experimental results applied on random graphs and we provide statistical evidence that our method outperforms a fast search-based drawing method (hill climbing) in execution time while it produces comparably good graph layouts. We also demonstrate the method on real world graph datasets to show that we can reproduce similar results in a real world setting.     

An efficient approach to determine cell formation,cell layout and intracellular machine sequence in cellular manufacturing systems

Cellular manufacturing systems (CMS) are used to improve production flexibility and efficiency. They involve the identification of part families and machine cells so that intercellular movement is minimized and the utilization of the machines within a cell is maximized. Previous research has focused mainly on cell formation problems and their variants; however, only few articles have focused on more practical and complicated problems that simultaneously consider the three critical issues in the CMS-design process, i.e., cell formation, cell layout, and intracellular machine sequence. In this study, a two-stage mathematical programming model is formulated to integrate the three critical issues with the consideration of alternative process routings, operation sequences, and production volume. Next, because of the combinatorial nature of the above model, an efficient tabu search algorithm based on a generalized similarity coefficient is proposed. Computational results from test problems show that our proposed model and solution approach are both effective and efficient. When compared to the mathematical programming approach, which takes more than 112 h (LINGO) and 1139 s (CPLEX) to solve a set of ten test instances, the proposed algorithm can produce optimal solutions for the same set of test instances in less than 12 s.     

用蚁群算法求解带平衡约束的圆形布局问题

采用启发式方法结合演化算法的思路求解带平衡约束的圆形布局问题.首先对传统优化模型进行调整,并探讨了调整的合理性;然后设计一种分步定位的布局方法,在此基础上利用蚁群算法寻优;最后利用局部搜索技术,在传统模型意义下对布局进行了改进.数值实验表明,算法的性能比目前已有的结果有较大的提高.     

基于遗传算法的毕业设计编排解决方法

针对高校毕业设计编排问题因为一直没有得到重视而使得导师和学生之间存在很多问题得不到解决,文章通过分层的方法,将毕业设计编排问题由常见的五维组合规划模型分解为两次三维组合,缩减了问题的规模。同时针对用传统遗传算法求解所存在的问题,提出对偶体编码方案,并利用交替进化的方法,对多个目标逐个循环优化。结果表明,这种方法很好地实现了模式定理,大大提高了求解速度。     

A simulation-based approach for the optimal design of signalling block layout in railway networks

To meet the growing demand in railway transportation, practitioners are more and more required to upgrade or substitute the signalling system in order to increase the capacity of the network. Existing approaches for the design of the signalling layout, usually tend to maximize the technological efficiency of the system by shortening the length of block sections, thus reducing the minimum line headway and the energy consumption but increasing investment costs. This paper presents a design approach addressed to identify the signalling layout which minimizes the investment and management costs, while respecting the required level of capacity. To solve this problem an innovative design framework is introduced which integrates a stochastic multi-train simulation model within a “black-box” optimization loop. Results obtained from an application to a real metro line confirm the effectiveness of such method in finding the solution which minimizes total costs for the line manager. A comparison with the block layout which maximizes the technological efficiency highlights that the obtained solution constitutes a satisfying trade-off between total costs and network performances.     

Unidirectional loop network layout by a LP heuristic and design of telecommunications networks

In this paper, we present a new linear programming-based heuristic procedure for optimal design of the unidirectional loop network layout problem. The heuristic procedure employs a linear programming formulation and solves the problem using the flow matrix of the unidirectional loop problem. To find an optimal solution, one can either generate all possible solutions or use a branch-and-bound procedure. But, both above methods require very high computational time and computer memory for larger problems. The heuristic developed in this paper is quite fast and obtains near optimal solutions. The heuristic procedure was tested on 16 different problems selected from the literature. The results showed that in most cases optimal—and in a few cases near optimal—solutions were obtained with very little computational time. Several examples are discussed. We also demonstrate that the above problem formulation and approach can be used to solve a special class of telecommunication networks where a set of computers (or processors) are attached by unidirectional point-to-point links around a loop.     

基于粒子群优化算法的约束布局优化

布局优化是NP难问题，也是复杂的非线性约束优化问题．针对这个问题，将新的基于粒子群优化的方法应用于布局参数的优化，提出了适合粒子群优化的约束处理，并通过与直接搜索算法的混合，加强了算法在局部区域的搜索能力．通过实例将该算法与乘子法以及基于遗传算法的布局优化方法进行了比较．仿真结果表明，该算法可以提高布局优化问题解的质量，同时降低计算费用．     

Multi-objective optimal fixture layout design

This paper addresses a major issue in fixture layout design to determine and evaluate the acceptable fixture designs based on multiple quality criteria and to select an optimal fixture with appropriate trade-offs among multiple performance requirements. The performance objectives considered are related to the fundamental requirements of kinematic localization and total fixturing (form-closure). Three performance objectives are defined as the workpiece localization accuracy and the norm and dispersion of the locator contact forces. The paper focuses on multi-criteria optimal design with a hierarchical approach. An efficient interchange algorithm is extended and used for different practical cases, leading to proper trade-off strategies for performing fixture synthesis. Examples are given to illustrate empirical observations with respect to the proposed approach and its effectiveness.     

Reliability optimization of topology communication network design using an improved ant colony optimization

Network design problem is a well-known NP-hard problem which involves the selection of a subset of possible links or a network topology in order to minimize the network cost subjected to the reliability constraint. To overcome the problem, this paper proposes a new efficiency algorithm based on the conventional ant colony optimization (ACO) to solve the communication network design when considering both economics and reliability. The proposed method is called improved ant colony optimizations (IACO) which introduces two addition techniques in order to improve the search process, i.e. neighborhood search and re-initialization process. To show its efficiency, IACO is applied to test with three different topology network systems and its results are compared with those obtained results from the conventional approaches, i.e. genetic algorithm (GA), tabu search algorithm (TSA) and ACO. Simulation results, obtained these test problems with various constraints, shown that the proposed approach is superior to the conventional algorithms both solution quality and computational time.     

Facility layout design using virtual multi-agent system

This paper presents a novel approach to the facility layout design problem based on multi-agent society where agents’ interactions form the facility layout design. Each agent corresponds to a facility with inherent characteristics, emotions, and a certain amount of money, forming its utility function. An agent’s money is adjusted during the learning period by a manager agent while each agent tries to tune the parameters of its utility function in such a way that its total layout cost can be minimized in competition with others. The agents’ interactions are formed based on market mechanism. In each step, an unoccupied location is presented to all applicant agents, for which each agent proposes a price proportionate to its utility function. The agent proposing a higher price is selected as the winner and assigned to that location by an appropriate space-filling curve. The proposed method utilizes the fuzzy theory to establish each agent’s utility function. In addition, it provides a simulation environment using an evolutionary algorithm to form different interactions among the agents and makes it possible for them to experience various strategies. The experimental results show that the proposed approach achieves a lower total layout cost compared with state of the art methods.     

矩形布局优化问题的局部搜索蜂群算法

带平衡约束的矩形布局问题属于组合优化问题,当问题规模增大时求解困难。为提高求解效率,设计了一个蜂群算法,通过分析解的分布,提供了基于贪心策略的群体初始化方案,选择了有效的变异算子,将蜂群算法的搜索空间聚焦于最优解可能的区域。另外设计了一个二次局部搜索算法,对解的质量进行进一步提升。在10个公开的案例上与目前性能最好的算法进行了对照,提出的蜂群算法在其中9个较大规模的案例上超过了现有算法。理论分析和实验结果表明,相对于现有算法,所提蜂群算法能明显提高求解效率。     

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.     

Optimum layout design of onshore wind farms considering stochastic loading

Renewable energy technologies are developing rapidly, while in the last decade great interest is encountered in the use of wind energy, especially due to the energy crisis and serious environmental problems appeared from the use of fossil fuels and therefore a large number of wind farms have been installed around the world. On the other hand the ability of nature inspired algorithms to efficiently handle combinatorial optimization problems was proved by their successful implementation in many fields of engineering sciences. In this study, a new problem formulation for the optimum layout design of onshore wind farms is presented, where the wind load is implemented using stochastic fields. For this purpose, a metaheuristic search algorithm based on a discrete variant of the harmony search method is used for solving the problem at hand. The farm layout problem is by nature a constrained optimization problem, and the contribution of the wake effects is significant; therefore, in two formulations presented in this study the influence of wind direction is also taken into account and compared with the scenario that the wake effect is ignored. The results of this study proved the applicability of the proposed formulations and the efficiency of combining metaheuristic optimization with stochastic wind loading for dealing with the problem of optimal layout design of wind farms.     

A tabu search-based algorithm for the fuzzy clustering problem

The Fuzzy Clustering Problem (FCP) is a mathematical program which is difficult to solve since it is nonconvex, which implies possession of many local minima. The fuzzy C-means heuristic is the widely known approach to this problem, but it is guaranteed only to yield local minima. In this paper, we propose a new approach to this problem which is based on tabu search technique, and aims at finding a global solution of FCP. We compare the performance of the algorithm with the fuzzy C-means algorithm.     

基于分层抽样的模拟禁忌混合智能优化算法TSII

将分层抽样随机模拟与禁忌搜索结合,构造了TS II模拟禁忌混合智能优化算法。随机模拟采用缩减方差、加速收敛的分层抽样技术,保证抽样遍布于整个搜索空间,避免禁忌搜索路径往返重复,克服禁忌搜索对初始解的依赖,算法同时使用禁忌表与希望表,将分散搜索与集中搜索相结合,增强算法的并行处理能力,提高寻优的效率与精度。Benchmark问题评测结果显示出了该算法的有效性。     

微粒群算法在产品组件布局设计中的应用

提出了一种基于微粒群算法的自适应优化布局求解算法,该算法以组件特征模型为基础,在微粒群算法中引入人机交互技术,从整体上自动优化布局方案,以满足约束条件为目标。并以手机组件的布局求解为例,对该算法进行了验证。理论和实例分析表明,该算法能有效地生成多个手机组件布局方案。     

A particle swarm optimization algorithm for the multiple-level warehouse layout design problem

Warehouse operation and management is one of the essential parts of manufacturing and service operations. The warehouse layout problem is a key to warehouse operations. Generally, warehouse layout design models attempt to optimize different objectives such as the orientation of storage racks, the allocation of space among competing uses, the number of cranes, the overall configuration of the facility, etc. The warehousing strategies can be classified as distribution-type, production-type and contract-type warehouse strategies. In this study, a distribution-type warehouse considered that various type products are collected from different suppliers for storing in the warehouse for a determined period and for delivery to different customers. The aim of the study is to design a multiple-level warehouse shelf configuration which minimizes the annual carrying costs. The turnover rates of the products are classified and they are considered while putting/picking them to/from shelves regarding the distances between the shelves and docks. Since proposed mathematical model was shown to be NP-hard, a particle swarm optimization algorithm (PSO) as a novel heuristic was developed for determining the optimal layout.     

Automatic layout of 2D free-form shapes based on geometric similarity feature searching and fuzzy matching

Two-dimensional (2D) irregular layout is widely applied in various manufacturing processes, such as sheet metal cutting, shipbuilding, and electronic component placement. An efficient layout algorithm can effectively improve the material utilization, thereby reducing manufacturing cost. But the free-form shape layout problem is very challenge as it is difficult to exactly represent a free-form shape. There is not an efficient method currently available for the 2D free-form shape layout. This paper proposes a method based on the geometric similarity feature searching and fuzzy matching for the 2D free-form shape layout. The freeman chain code is developed to describe the contour information of shapes and forward-lines to form the basis of the layout strategy. A strategy based on fuzzy matching is proposed for the layout, which includes searching geometric similarity features using the longest common subsequence and the proposed placement algorithm to complete the collision. Three computational experiments are conducted to analyze the performance of the proposed method. Experimental results show that the proposed method is feasible and effective with the good applicability to achieve a high filling rate in reduced time.