An integrated logarithmic fuzzy preference programming based methodology for optimum maintenance strategies selection

Selecting optimum maintenance strategies plays a key role in saving cost, and improving the system reliability and availability. Analytic hierarchical process (AHP) is widely used for maintenance strategies selection in the Multiple Criteria Decision-Making (MCDM) field. But the traditional or hybrid AHP methods either produce multiple, even conflict priority results, or have complicated algorithm structures which are unstable to obtain the optimum solution. Therefore, this paper proposes an integrated Logarithmic Fuzzy Preference Programming (LFPP) based methodology in AHP to solve the optimum maintenance strategies selection problem. The multiplicative constraints and deviation variables are applied instead of additive ones to utilize both qualitative and quantitative data, and process the upper and lower triangular fuzzy judgments to obtain the same priorities. The proposed methodology can produce the unique normalized optimal priority vector for fuzzy pairwise comparison matrices, and it is capable of processing all comparison matrices to obtain the global priorities simultaneously and directly in the form of super-matrix according to the different requirements and judgments of decision-makers. Finally, an example is provided to demonstrate the feasibility and validity of the proposed methodology.     

Fuzzy MCDM approach for selecting the best environment-watershed plan

In the real word, the decision-making problems are very vague and uncertain in a number of ways. Most of the criteria have interdependent and interactive features, so they cannot be evaluated by conventional measure method. Such as the feasibility, thus, to approximate the human subjective evaluation process, it would be more suitable to apply a fuzzy method in the environment-watershed plan topic. This paper describes the design of a fuzzy decision support system in multi-criteria analysis approach for selecting the best plan alternatives or strategies in environment watershed. The fuzzy analytic hierarchy process (FAHP) method is used to determine the preference weightings of criteria for decision makers by subjective perception (natural language). A questionnaire was used to find out from three related groups comprising 15 experts, including 5 from the university of expert scholars (include Water Resources Engineering and Conservation, Landscape and Recreation, Urban Planning, Environment Engineering, Architectural Engineering, etc.), 5 from the government departments, and 5 from industry. Subjectivity and vagueness analysis is dealt with the criteria and alternatives for selection process and simulation results by using fuzzy numbers with linguistic terms. It incorporated the decision-makers’ attitude towards the preference; overall performance value of each alternative can be obtained based on the concept of fuzzy multiple-criteria decision-making (FMCDM). This research also gives an example of evaluation consisting of five alternatives, solicited from an environment-watershed plan work in Taiwan, is illustrated to demonstrate the effectiveness and usefulness of the proposed approach. The result is useful for destination planning and the sustainability of watershed tourism resources as well.     

Hybrid strategy for selecting compact set of clustering partitions

The selection of the most appropriate clustering algorithm is not a straightforward task, given that there is no clustering algorithm capable of determining the actual groups present in any dataset. A potential solution is to use different clustering algorithms to produce a set of partitions (solutions) and then select the best partition produced according to a specified validation measure; these measures are generally biased toward one or more clustering algorithms. Nevertheless, in several real cases, it is important to have more than one solution as the output. To address these problems, we present a hybrid partition selection algorithm, HSS, which accepts as input a set of base partitions potentially generated from clustering algorithms with different biases and aims, to return a reduced and yet diverse set of partitions (solutions). HSS comprises three steps: (i) the application of a multiobjective algorithm to a set of base partitions to generate a Pareto Front (PF) approximation; (ii) the division of the solutions from the PF approximation into a certain number of regions; and (iii) the selection of a solution per region by applying the Adjusted Rand Index. We compare the results of our algorithm with those of another selection strategy, ASA. Furthermore, we test HSS as a post-processing tool for two clustering algorithms based on multiobjective evolutionary computing: MOCK and MOCLE. The experiments revealed the effectiveness of HSS in selecting a reduced number of partitions while maintaining their quality.     

Application of a new multi-agent Hybrid Co-evolution based Particle Swarm Optimisation methodology in ship design

In this paper, a multiple objective ‘Hybrid Co-evolution based Particle Swarm Optimisation’ methodology (HCPSO) is proposed. This methodology is able to handle multiple objective optimisation problems in the area of ship design, where the simultaneous optimisation of several conflicting objectives is considered. The proposed method is a hybrid technique that merges the features of co-evolution and Nash equilibrium with a ε-disturbance technique to eliminate the stagnation. The method also offers a way to identify an efficient set of Pareto (conflicting) designs and to select a preferred solution amongst these designs. The combination of co-evolution approach and Nash-optima contributes to HCPSO by utilising faster search and evolution characteristics. The design search is performed within a multi-agent design framework to facilitate distributed synchronous cooperation. The most widely used test functions from the formal literature of multiple objectives optimisation are utilised to test the HCPSO. In addition, a real case study, the internal subdivision problem of a ROPAX vessel, is provided to exemplify the applicability of the developed method.     

A human reliability assessment of marine auxiliary machinery maintenance operations under ship PMS and maintenance 4.0 concepts

Cognition, Technology & Work - Maintenance is one of the core technical aspects on board ships, which is required for the ready availability, reliability, and efficiency of machinery equipment....     

Hybrid shape parameter strategy for the RBF approximation of vibrating systems

Shape parameters play an important role in radial basis function (RBF) approximations. Therefore, the choice of them is an active field in numerical analysis research. In this paper, first we review the available strategies in the literature for selecting shape parameters. Then, we introduce an alternative approach called hybrid strategy for scaling the RBFs. This strategy is constructed based on the advantages of the older ones and discards their disadvantages. The efficiency of the new strategy is demonstrated by comparing the effects of different strategies on approximating the eigenvalues of ordinary and partial differential equations with different boundary conditions.     

Application of a new combined intuitionistic fuzzy MCDM approach based on axiomatic design methodology for the supplier selection problem

Evaluating and selecting a suitable supplier is a complex problem which involves a number of different criteria. In literature, there are various multi-criteria decision making (MCDM) methods available with their own characteristic features. The focus of this study is intuitionistic fuzzy (IF) MCDM methods which have attracted much attention from academics and practitioners in recent years. IF sets are widely used to tackle imprecise and uncertain decision information in decision making due to their capability of accommodating the hesitation in human decision processes. This study proposes a new integrated methodology that is used for the first time in the literature. This approach consists of intuitionistic fuzzy analytic hierarchy process (IFAHP), an MCDM technique, for determining the weights of supplier evaluation criteria, and the concept of intuitionistic fuzzy axiomatic design (IFAD) principles for ranking competing supplier alternatives with respect to their overall performance. Decision makers’ assessments and opinions are extended to the IF environment in this approach and furthermore, the group decision making (GDM) approach is utilized in order to overcome uncertainties and vagueness, minimize the partiality of decision process and to avoid bias. This study contributes to supplier selection and IF sets literature by providing a combined framework based on IFAHP and IFAD methodology for the first time. To assess the validity of the proposed integrated IF MCDM approach, a case study from Turkey is provided. This study can be useful to researchers in better understanding the supplier selection problem theoretically, as well as to organizations in designing better satisfying supplier evaluation systems.     

改进遗传算法的WSN节点最优路由选择策略

针对无线传感器节点数据传输过程中的能量消耗问题,为了提高节点数据传输实时性,提出一种改进遗传算法的无线传感器网络节点最优路由选择策略。根据无线传感器网络的拓扑结构将监测区域划分不同大小的簇,并根据节点剩余能量选择每一个簇的簇头节点,然后将簇头节点编码成遗传算法的个体,根据数据转发能量耗能和延迟时间构建个体的适应度函数,并通过模拟自然界生物进化过程中的选择、交叉、变异等操作,找到节点数据转发的最优路径,在Matlab 2012平台上对数据路由算法的性能进行仿真测试。仿真结果表明,相对其他路由选择策略,提出的路由选择策略不仅可以均衡各个传感器节点的剩余能量,而且大幅度减少了数据转发路由过程中的能量消耗和延迟时间。     

Genetic algorithm based methodology for breaking the steganalytic systems.

Steganalytic techniques are used to detect whether an image contains a hidden message. By analyzing various image features between stego-images (the images containing hidden messages) and cover-images (the images containing no hidden messages), a steganalytic system is able to detect stego-images. In this paper, we present a new concept of developing a robust steganographic system by artificially counterfeiting statistic features instead of the traditional strategy by avoiding the change of statistic features. We apply genetic algorithm based methodology by adjusting gray values of a cover-image while creating the desired statistic features to generate the stego-images that can break the inspection of steganalytic systems. Experimental results show that our algorithm can not only pass the detection of current steganalytic systems, but also increase the capacity of the embedded message and enhance the peak signal-to-noise ratio of stego-images.     

Computer aided reliability for optimum maintenance planning

Computer aided Maintenance planning for mechanical equipment is presented in this work to implement the optimized extensive maintenance plan at a specific time horizon. The objective is to interchange the unscheduled corrective maintenance into scheduled preventive maintenance depending on historical data of equipment. This work is concerned with development of reliability analysis based on Weibull distribution. An optimization technique has been developed to provide the optimized preventive maintenance plan for the whole equipment during a required time horizon.     

A development methodology for embedded systems based on RT-DEVS

This work is concerned with modelling, analysis and implementation of embedded control systems using RT-DEVS, i.e. a specialization of classic discrete event system specification (DEVS) for real-time. RT-DEVS favours model continuity, i.e. the possibility of using the same model for property analysis (by simulation or model checking) and for real time execution. Special case tools are reported in the literature for RT-DEVS model analysis and design. In this work, temporal analysis of a model exploits a translation in Uppaal timed automata for exhaustive verification. For large models a simulator was realized in Java which directly stems from RT-DEVS operational semantics. The same concerns are at the basis of a real-time executive. The paper describes the proposed RT-DEVS development methodology and clarifies its implementation status. The approach is demonstrated by applying it to an embedded system example which is analyzed through model checking and implemented in Java. Finally, research directions which deserve further work are indicated.     

基于RIPPER的旋转机械故障诊断知识获取

数据挖掘技术能够从大量、不完全、有噪声、模糊、随机的实际应用数据中,提取隐含在其中的、人们事先不知道的本质的规律。为了有效地发现旋转机械故障诊断过程中的故障征兆知识,引入数据挖掘技术和方法。针对旋转机械,构建了基于重复增量修枝算法RIPPER（Repeated Incremental Pruning to Produce Error Reduction）的故障诊断知识获取系统。通过收集故障现象并整理成由故障征兆、故障类型等组成的故障信息样本,应用RIPPER算法对故障进行分析得到故障诊断规则集文件,实现故障诊断系统知识的获取和自动更新,并能对旋转机械的常见故障进行诊断,验证了算法的合理性。     

基于最佳相位匹配的减摇鳍低航速控制策略

为了满足工程船舶对低航速下减摇的需求,提高船舶在锚泊和低航速下的耐波性,提出减摇鳍在低航速下的控制策略,重点针对低航速下升力与鳍角之间相位关系对航速十分敏感的问题和船舶横摇模型的不确定性问题进行研究.通过数值迭代解决低航速下升力相位对航速的敏感性和升力与鳍角的非线性关系问题,相位调节器可以克服航速测量误差的影响,保证最...     

基于缓存与指针推进的混合移动性管理策略

提出了一种将缓存策略与指针推进策略结合的混合位置管理策略(记为HCF策略),通过利用移动用户移动的移动性以及接受呼入的局部性,在缓存信息失效的情况下,可通过遍历起始于缓存中的推进指针链来获得移动用户的位置信息,从而避免直接访问归属位置寄存器HLR(Home Location Register)数据库。因此,该策略可有效的减少对HLR的访问,减少位置管理中的通信流量。实验结果显示,当一个移动用户的呼叫-移动率较高CMR(Call-to-Mobility Ratio)或HLR的通信流量较大时,提出的策略优于基本策略和现有的缓存策略。     

Harmony search based algorithm for the optimum design of grillage systems to LRFD-AISC

Harmony search based optimum design method is presented for the grillage systems. This numerical technique imitates the musical performance process that takes place when a musician searches for a better state of harmony. Jazz improvisation seeks to find musically pleasing harmony similar to the optimum design process which seeks to find the optimum solution. The design algorithm considers the serviceability and ultimate strength constraints which are implemented from Load and Resistance Factor Design—American Institute of Steel Construction (LRFD-AISC). It selects the appropriate W-sections for the transverse and longitudinal beams of the grillage system out of 272 discrete W-section designations given in LRFD-AISC. This selection is carried out such that the design limitations described in LRFD-AISC are satisfied and the weight of the system is the minimum. Many design examples are considered to demonstrate the efficiency of the algorithm presented.     

Risk based opportunistic maintenance model for complex mechanical systems

The essence of the complex mechanical system can be considered as an open system. There exist coupling relationships between various parts in the system and also between different fault modes, which result in multiple fault propagation paths. Considering the safety, benefits and maintenance loss, parameters such as downtime losses, minimal repair costs, corrective, preventive and opportunistic maintenance costs, should be analyzed comprehensively to investigate the influence of different maintenance strategies.A new risk based opportunistic maintenance (RBOM) model considering failure risk is proposed in the paper. It helps to convert the negative random factors caused by single faults to a favorable opportunity of preventive defense against failure for other slight degraded components in advance, so the overall economic losses could be reduced. The global optimization algorithm is further developed to realize RBOM policy. Case studies are provided to illustrate the proposed approaches, with sensitivity analysis of the position, time, style and criterion of the RBOM strategy. Comparative study with the widely used maintenance policy demonstrates the advantage of the proposed method can significantly reduce the maintenance cost and failure risk, and are expected to bring immediate benefits to the energy industry.     

An intelligent condition-based maintenance platform for rotating machinery

Maintenance is of necessity for sustaining machinery availability and reliability in order to ensure productivity, product quality, on-time delivery, and safe working environment. The costly maintenance strategies such as corrective maintenance and scheduled maintenance have been progressively replaced by superior maintenance strategies in which condition-based maintenance (CBM) is one of the delegates. This strategy commonly consists of sequent modules such as data acquisition, signal processing, feature extraction and feature selection, condition monitoring, etc. However, approaches in literature which have been developed for each module and implemented for different applications are standalone instead of a comprehensive system. Furthermore, these approaches have been demonstrated in a laboratory environment without any industrial validations. For these reasons, an intelligent algorithm based CBM platform is proposed in this paper to be applied for rotating machinery easily and effectively. Subsequently, two case-studies are presented in order to evaluate the effectiveness of this platform in industrial applications.     

An economic design for optimum maintenance float policy

This paper introduces a cost model to solve for optimum maintenance float policy. The model is based on an iterative solution developed for closed queuing maintenance networks. The use of this approach makes it possible to solve and obtain closed form solutions to maintenance float problems when all the centers in the network are exponentially distributed. A computer program is developed for the cost model. The program searches through a three-dimensional cost surface for the optimum solution. On reaching the optimum, the optimum policy as well as the maintenance float performance measures are generated. The computer program offers a decision support mechanism for the maintenance manager by making maintenance float information readily available, providing a more expedient alternative to simulation.     

基于模式更新的实视图一致性维护策略

通过定义不同数据源更新之间的并发依赖关系和同源依赖关系,利用概念化事务模型可实现松散耦合环境中视图的并发维护。在此基础上,提出VMSCNF算法,解决不稳定网络环境中基于模式更新的实视图一致性维护问题,并通过实验原型验证了算法有效性。