Improved decision rules in a combined system for minimizing job tardiness

In a recent article, Miyazaki described a combined system for setting due dates and sequencing jobs in order to reduce tardiness in a job shop. This paper interprets the major features of that system in the context of current research and suggests improvements in both components of the system.     

Application of rough sets for environmental decision support in industry

Practical environmental decision-making in industry is a complex task that often entails a subtle interplay between alternatives and criteria. Quantitative tools are used to aid decision-makers to arrive at rational conclusions. However, conventional decision aids are often limited by the need to define a priori weights for the criteria being considered; identifying the correct weights to use is not a trivial task and has been the subject of considerable research. An alternative approach based on rough set methodology is described in this work. The procedure develops an empirical, rule-based model from example responses derived from an expert panel. The model can then be used for decision-making in cases resembling the example used previously. Rough set theory also provides numerical measures of the reliability of the rule-based model developed. The approach is illustrated with two case studies, the first involving comparison of alternative energy sources, and the second involving the ranking of pollution prevention strategies in manufacturing.     

A method combining rules with genetic algorithm for minimizing makespan on a batch processing machine with preventive maintenance

This paper considers the problem of minimising makespan on a single batch processing machine with flexible periodic preventive maintenance. This problem combines two sub-problems, scheduling on a batch processing machine with jobs’ release dates considered and arranging the preventive maintenance activities on a batch processing machine. The preventive maintenance activities are flexible but the maximum continuous working time of the machine, which is allowed, is determined. A mathematical model for integrating flexible periodic preventive maintenance into batch processing machine problem is proposed, in which the grouping of jobs with incompatible job families, the starting time of batches and the preventive maintenance activities are optimised simultaneously. A method combining rules with the genetic algorithm is proposed to solve this model, in which a batching rule is proposed to group jobs with incompatible job families into batches and a modified genetic algorithm is proposed to schedule batches and arrange preventive maintenance activities. The computational results indicate the method is effective under practical problem sizes. In addition, the influences of jobs’ parameters on the performance of the method are analyzed, such as the number of jobs, the number of job families, jobs’ processing time and jobs’ release time.     

粗糙集中不确定性测量的修正粗糙熵方法

分析了引起粗糙集中不确定性的因素，对已有的测量不确定性的粗糙度与粗糙熵方法进行了比较，提出了一种修正的粗糙熵方法，证明了此粗糙熵的性质，并将基于等价关系的修正粗糙熵拓展到基于一般二元关系下的广义修正粗糙熵，同时给出了广义修正粗糙熵的定义及性质．通过分析和实例可以看出，所提出的修正粗糙熵方法可以用来更合理、更精确地测量粗糙集中的不确定性．     

A scatter search approach with dispatching rules for a joint decision of cell formation and parts scheduling in batches

A joint decision of cell formation and parts scheduling is addressed for a cellular manufacturing system where each type of machine and part may have multiple numbers and parts must require processing and transferring in batches. The joint decision problem is not only to assign batches and associated machine groups to cells, but also to sequence the processing of batches on each machine in order to minimise the total tardiness penalty cost. A nonlinear mixed integer programming mathematical model is proposed to formulate the problem. The proposed model, within nonlinear terms and integer variables, is difficult to solve efficiently for real size problems. To solve the model for practical purposes, a scatter search approach with dispatching rules is proposed, which considers two different combination methods and two improvement methods to further expand the conceptual framework and implementation of the scatter search so as to better fit the addressed problem. This scatter search approach interactively uses a combined dispatching rule to solve a scheduling sub-problem corresponding to each integer solution visited in the search process. A computational study is performed on a set of test problems with various dimensions, and computational results demonstrate the effectiveness of the proposed approach.     

A branch-and-bound algorithm for a two-stage hybrid flowshop scheduling problem minimizing total tardiness

A two-stage hybrid flowshop-scheduling problem is considered with the objective of minimizing total tardiness of jobs. In the hybrid flowshop, there is one machine at the first stage and multiple identical parallel machines at the second stage. Dominance properties and lower bounds are developed for the problem and a branch-and-bound algorithm is suggested using them. Results of computational experiments show that the suggested algorithm can find optimal solutions for problems with up to 15 jobs in a reasonable amount of central processing unit time.     

A new algorithm for minimizing surplus parts in selective assembly by using genetic algorithm

Precision assemblies are produced from low precision subcomponents by partitioning and assembling them randomly from their corresponding groups. Surplus part is one of the important issues, which reduces the implementation of selective assembly in real situations. A new algorithm is introduced in this present paper to reduce surplus parts almost to zero and it is achieved in two stages by using a genetic algorithm. For demonstrating the proposed algorithm, a gearbox shaft assembly is considered as an example problem in which the shaft and pulley are manufactured in wider tolerance and partitioned in three to nine bins. The surplus parts are divided into three bins equally and a best combination of groups is obtained for both cases. It is observed that nearly 995 assemblies are produced out of one thousand subcomponents with the manufacturing cost savings of 19.5% for T _max and 992 assemblies are produced with 13.5% saving in manufacturing cost for 0.9T _max.     

Pattern clustering with statistical methods using a DNA-based algorithm

Clustering is commonly exploited in engineering, management, and science fields with the objective of revealing structure in pattern data sets. In this article, through clustering we construct meaningful collections of information granules (clusters). Although the underlying goal is obvious, its realization is fully challenging. Given their nature, clustering is a well-known NP-complete problem. The existing algorithms commonly produce some suboptimal solutions. As a vehicle of pattern clustering, we discuss in this article how to use a DNA-based algorithm. We also discuss the details of encoding being used here with statistical methods combined with the DNA-based algorithm for pattern clustering.     

A DNA-based approach to the carbon nanotube sorting problem

Carbon nanotube sorting, i.e., the separation of a mixture of tubes into different electronic types and further into species with a specific chirality, is a fascinating problem of both scientific and technological importance. It is one of those problems that are easy to describe but difficult to solve. Single-stranded DNA forms stable complexes with carbon nanotubes and disperses them effectively in water. A particular DNA sequence of alternating guanine (G) and thymine (T) nucleotides ((GT) _n , with n = 10 to 45) self-assembles into an ordered supramolecular structure around an individual nanotube, in such a way that the electrostatic properties of the DNA-carbon nanotube hybrid depend on tube structure, enabling nanotube separation by anion-exchange chromatography. This review provides a summary of the separation of metallic and semiconducting tubes, and purification of single (n, m) tubes using the DNA-wrapping approach. We will present our current understanding of the DNA-carbon nanotube hybrid structure and separation mechanisms, and predict future developments of the DNA-based approach. This article is published with open access at Springerlink.com     

Dispatching rules in scheduling Dispatching rules in scheduling: a fuzzy approach

Job-shop scheduling through simulation uses various kinds of dispatching rules such as SPT or the slack time rule. Each of these rules aims at satisfying a single criterion although workshop management is a multi-criteria problem. This paper proposes a way to use fuzzy logic in order to build aggregated rules allowing to obtain a compromise between the satisfaction of several criteria. When the criteria of performance change with the evolution of the production environment, these aggregated rules can be parametrized in order to modify the respective influence of the elementary rules they are composed of.     

基于广义粗糙集的知识约简方法研究

针对粗糙集理论在知识约简中的实际需要,提出了建立在一般二元关系基础上的广义粗糙集知识约简方法。首先证明了广义粗糙集是经典粗糙集的一般性推广,而经典粗糙集是广义粗糙集的特例;然后以一般二元关系为分类基础,给出一般关系决策系统中的知识约简判定定理和辨识矩阵;最后根据实例提取最小的属性集,验证了该方法的实用性。该方法摆脱了二元等价关系对经典粗糙集的困扰,既保证了粗糙集理论在知识发现研究中的理论优势,又拓展了粗糙集理论在实际应用中的适用范围,具有较强的实用性。     

一种面向大规模特征集的高效特征匹配算法

针对传统特征匹配(网络和信息安全系统的核心技术)算法的性能随着特征集规模的不断增大而不断下降的问题,提出了一种面向大规模特征集的高效特征匹配算法ALPM.该算法基于传统算法WM的跳跃思想,并结合硬件体系结构的特点,对预处理过程和匹配过程分别采用了不同的优化策略,如采用不同的哈希函数索引Shift表和Hash表,在预处理过程中动态截取特征标志,在匹配过程中结合Cache大小和特征集规模调整哈希函数冲突概率等,以提高匹配的性能.实验结果表明,针对大规模特征集,ALPM算法匹配性能比经典算法提高5～10倍.     

基于模糊粗糙集和鲸鱼优化支持向量机的化工过程故障诊断

针对化工过程复杂,故障数据量大、属性多,难以保证故障诊断准确率和速度的问题,提出了一种基于模糊粗糙集(fuzzy rough sets,FRS)和鲸鱼优化的支持向量机(support vector machine,SVM)的化工过程故障诊断方法.通过对化工过程历史数据分析,判别故障类型.首先,利用模糊粗糙集对离散化后的...     

Genetic algorithm for minimizing assembly variation in selective assembly

Selective assembly is a method of obtaining high-precision assemblies from relatively low-precision components. In selective assembly, the mating parts are manufactured with wide tolerances. The mating part population is partitioned to form selective groups, and corresponding selective groups are then assembled interchangeably. If the mating parts are manufactured in different processes and in different machines, their standard deviations will be different. It is impossible that the number of parts in the selective group will be the same. A large number of surplus parts are expected according to the difference in the standard deviations of the mating parts. A method is proposed to find the selective groups to minimize the assembly variation and surplus parts when the parts are assembled linearly. A genetic algorithm is used to find the best combination of the selective groups to minimize the assembly variation. Selective assembly is successfully applied using a genetic algorithm to achieve high-precision assemblies without sacrificing the benefit of wider tolerance in manufacturing.     

面向数据流的敏感规则k-匿名保护算法

为了使攻击者通过降低阈值来发现被隐藏规则的概率小于1/k,以此实现对敏感规则的二重保护,提出了一种面向数据流的敏感规则k-匿名保护算法.该算法首先用时间滑动窗口技术来获取数据使用者最感兴趣的最新n个时刻到达的数据,然后通过追加交易的方式而并非修改交易项的方式来实现对敏感规则的k-匿名,从而避免对数据流的二次访问以及被隐藏敏感规则的泄漏.同时采用素数编码的方法,用素数集代替原始项集参与运算,以提高算法的效率和降低算法的空间复杂度.实验结果表明,此算法可以在数据流环境下高效进行敏感规则的k-匿名,并且能够保证挖掘结果的有用性.     

A new approach to propellant formulation: minimizing life-cycle costs through science-based design

 The traditional approach to developing propellants for specific gun applications relies heavily on trial and error. Candidate formulations must be made in small quantities and subjected to burning-rate measurements and small-scale vulnerability assessments. If the properties of these candidates fail to meet expectations, the process must be repeated. This approach, while historically unavoidable, is obviously inefficient in time and expense, but it also can generate considerable waste streams associated with unsuccessful formulations. With added considerations of life-cycle costs including environmental impact at all stages of development, use, and disposal, this traditional approach becomes increasingly unworkable. In this report a new approach is proposed which makes maximal use of scientific understanding embodied in models during the early phases of the propellant-development cycle. Through simple simulations, it is shown that this strategy can have a significant impact on the overall costs of the development process. In analogy to the DOE program to convert the nuclear-weapon stewardship from testing-based to science-based, we term the new approach "science-based design." It is argued that the modeling contribution to the propellant-development process is most efficiently implemented by subjecting candidate formulations to a hierarchy of models of different sophistication and input-data requirements, reserving the most rigorous models (usually the most data-intensive and least robust) for the most promising candidates. This new approach will require concentration and leveraging of resources toward the most critical early-phase development steps, but it may be the only credible strategy to reconcile the need for higher-performance weapons with the reality of declining resources. Received: 2 August 1999 / Accepted: 10 November 1999     

A consistent approach for fluid-structure-contact interaction based on a porous flow model for rough surface contact

Simulation approaches for fluid-structure-contact interaction, especially if requested to be consistent even down to the real contact scenarios, belong to the most challenging and still unsolved problems in computational mechanics. The main challenges are 2-fold—one is to have a correct physical model for this scenario, and the other is to have a numerical method that is capable of working and being consistent down to a zero gap. Moreover, when analyzing such challenging setups of fluid-structure interaction, which include contact of submersed solid components, it gets obvious that the influence of surface roughness effects is essential for a physical consistent modeling of such configurations. To capture this system behavior, we present a continuum mechanical model that is able to include the effects of the surface microstructure in a fluid-structure-contact interaction framework. An averaged representation for the mixture of fluid and solid on the rough surfaces, which is of major interest for the macroscopic response of such a system, is introduced therein. The inherent coupling of the macroscopic fluid flow and the flow inside the rough surfaces, the stress exchange of all contacting solid bodies involved, and the interaction between fluid and solid are included in the construction of the model. Although the physical model is not restricted to finite element–based methods, a numerical approach with its core based on the cut finite element method, enabling topological changes of the fluid domain to solve the presented model numerically, is introduced. Such a cut finite element method–based approach is able to deal with the numerical challenges mentioned above. Different test cases give a perspective toward the potential capabilities of the presented physical model and numerical approach.     

Colorimetric sensitivity of gold nanoparticles: minimizing interparticular repulsion as a general approach

GNPs (gold nanoparticles) as an eye-catching sensor rely on the high extinction coefficients and the shift of the surface plasmon band which signals the disperse-to-aggregate transformation. The selectivity of the sensors is dictated by the surface functionality whose density presumably has a positive correlation with the sensitivity toward the targeted analyte. To improve the analytical performance, most efforts in this research field focus on the design and synthesis of the sensing elements as well as on the increase in density on GNPs. Proposed here is an alternative rationale that the further improvement of the GNP sensitivity can be achieved by minimizing the electrostatic repulsion and hence the energy barrier for the recognition event to take place. Our model system begins with thioctic acid-stabilized GNPs which are subsequently modified with 15-crown-5 ether for the recognition toward K (+). For a given coverage of 15-crown-5 ether, the limits of detection (LODs) can be improved by more than 3 orders of magnitude via adjusting the solution pH and ionic strength which we suggest a general guideline for the optimization of a new GNP sensing scheme. Following this guideline, satisfactory performance with LODs at the micromolar level can be systematically and efficiently found for GNPs with a range of 15-crown-5 ether coverage.     

Flower pollination algorithm: A novel approach for multiobjective optimization

Multiobjective design optimization problems require multiobjective optimization techniques to solve, and it is often very challenging to obtain high-quality Pareto fronts accurately. In this article, the recently developed flower pollination algorithm (FPA) is extended to solve multiobjective optimization problems. The proposed method is used to solve a set of multiobjective test functions and two bi-objective design benchmarks, and a comparison of the proposed algorithm with other algorithms has been made, which shows that the FPA is efficient with a good convergence rate. Finally, the importance for further parametric studies and theoretical analysis is highlighted and discussed.     

A multicriteria evolutionary algorithm for mechanical design optimization with expert rules

This paper addresses the problem of optimizing mechanical components during the first stage of the design process. While a previous study focused on parameterized designs with fixed configurations—which led to the development of the PAMUC (Preferences Applied to Multiobjectivity and Constraints) method, to tackle constraints and preferences in evolutionary algorithms (EAs)—, the models to be considered in this work are enriched by the presence of topological variables. In this context, in order to create optimal but also realistic designs, i.e. fulfilling not only technical requirements but also technological constraints (more naturally expressed in terms of rules), a novel approach is proposed: PAMUC II. It consists in integrating an inference engine within the EA to repair the individuals violating the user‐defined rules. PAMUC II is tested on mechanical benchmarks, and provides very satisfactory results in comparison with a weighted sum method with penalization to deal with the constraints. Copyright © 2004 John Wiley & Sons, Ltd.