Performance Evaluation Problem Research Articles

A dynamic multiple attribute decision making model with learning of fuzzy cognitive maps

This paper concerns with a new multiple attribute decision making (MADM) model to cope with temporal performance of alternatives during different time periods. Dynamic MADM problems has grabbed remarkable attention of decision analysis community in recent years. In parallel with the recent advances in information technologies, firms steadily recognize the importance of data, and business analytics solutions is about to become standard business practice. Majority of the dynamic MADM literature deals with combining past and present data by means of aggregation operators. There is a research gap in developing data-driven methodologies to capture the patterns and trends in the historical data, and provide decision makers with meaningful insights in decision making practices. Analogous with the fact that style of decision making evolving from intuition-based to data-driven, this study proposes a new dynamic MADM model by learning of fuzzy cognitive maps (FCMs) to support decision makers in making informed decisions by considering future performance of alternatives. According to proposed model, Jaya algorithm, a simple and effective metaheuristic optimization method, is used to train FCMs to capture the patterns in historical data. Then, short-, medium-, and long-term future decision making matrices are generated. Finally, past, current and future decision making matrices are taken into consideration, and ranking of alternatives are obtained based on closeness coefficients. The proposed model is realized in a real-life supplier performance evaluation problem.

Novel Code Plagiarism Detection Based on Abstract Syntax Tree and Fuzzy Petri Nets

Those students who major in computer science and/or engineering are required to design program codes in a variety of programming languages. However, many students submit their source codes they get from the Internet or friends with no or few modifications. Detecting the code plagiarisms done by students is very time-consuming and leads to the problems of unfair learning performance evaluation. This paper proposes a novel method to detect the source code plagiarisms by using a high-level fuzzy Petri net (HLFPN) based on abstract syntax tree (AST). First, the AST of each source code is generated after the lexical and syntactic analyses have been done. Second, token sequence is generated based on the AST. Using the AST can effectively detect the code plagiarism by changing the identifier or program statement order. Finally, the generated token sequences are compared with one another using an HLFPN to determine the code plagiarism. Furthermore, the experimental results have indicated that we can make better determination to detect the code plagiarism.

Towards understanding the effectiveness of patch injection

To contain the prevalence of computer virus on a network, we have to continuously inject new patches into the network. As the limited communication bandwidth restricts the patch injection rate, we need to evaluate the performance of a patch injection rate in restraining computer infections. This paper focuses on the performance evaluation problem. We propose a virus–patch interacting model with patch injection mechanism, and show that this model admits a globally stable equilibrium. This result implies that the fraction of infected nodes will approach a common value. Therefore, we recommend the asymptotic fraction of infected nodes to serve as a measure of performance of the associated patch injection rate. We also examine the influence of different parameters on the asymptotic fraction of infected nodes. In particular, we find that patch injection is particularly effective for densely connected networks. This work takes the first step towards understanding the effectiveness of patch injection.

Optimizing Artificial Neural Networks For The Evaluation Of Asphalt Pavement Structural Performance

Artificial Neural Networks represent useful tools for several engineering issues. Although they were adopted in several pavement-engineering problems for performance evaluation, their application on pavement structural performance evaluation appears to be remarkable. It is conceivable that defining a proper Artificial Neural Network for estimating structural performance in asphalt pavements from measurements performed through quick and economic surveys produces significant savings for road agencies and improves maintenance planning. However, the architecture of such an Artificial Neural Network must be optimised, to improve the final accuracy and provide a reliable technique for enriching decision-making tools. In this paper, the influence on the final quality of different features conditioning the network architecture has been examined, for maximising the resulting quality and, consequently, the final benefits of the methodology. In particular, input factor quality (structural, traffic, climatic), “homogeneity” of training data records and the actual net topology have been investigated. Finally, these results further prove the approach efficiency, for improving Pavement Management Systems and reducing deflection survey frequency, with remarkable savings for road agencies.

Benchmarking the performance of dairy products in Chinese dairy industry

PurposeThe purpose of this paper is to present a review of the main factors that are important to consumers of dairy products and develop a new product performance index for evaluating and benchmarking the performance of dairy products. This helps dairy product companies understand their dairy products’ overall performance level, relative to other dairy products in the market.Design/methodology/approachA new product performance index is developed for evaluating and benchmarking the performance of dairy products with respect to multiple criteria. Seven important criteria are identified for evaluating and benchmarking the performance of dairy products. To deal with the subjective assessments of qualitative performance measures, linguistic terms approximated by fuzzy numbers are used. Based on the concept of the degree of dominance, a fuzzy multicriteria group decision-making approach is developed to obtain a product performance index for each dairy product.FindingsThe proposed multicriteria group decision-making approach is found to be useful and effective in evaluating and benchmarking the performance of dairy products. The approach is capable of adequately considering the presence of multiple decision makers, the multi-dimensional nature of the performance evaluation problem, and modeling the subjectiveness and imprecision of the performance evaluation process.Research limitations/implicationsThe outcome of the multicriteria group decision-making approach is dependent on the subjective inputs provided by the decision makers.Practical implicationsThis product performance index will provide useful insights for companies understand their strengths and weaknesses in terms of their products’ performance criteria, and identify relevant areas for continuous improvement. This product performance index is also applicable for dealing with the general multicriteria decision-making problems.Social implicationsThe proposed multicriteria group decision-making approach can be used as a decision-making tool for providing various decision makers in dairy product companies and general consumers with useful information regarding the performance of different dairy products.Originality/valueThis paper highlights the important factors for evaluating and benchmarking dairy products and develops a new product performance index for evaluating and benchmarking the performance of dairy products in China.

Reinforced cuckoo search algorithm-based multimodal optimization

This work proposes a Reinforced Cuckoo Search Algorithm (RCSA) for multimodal optimization, which comprises three different strategies: modified selection strategy, Patron-Prophet concept, and self-adaptive strategy. The modified selection strategy has been proposed for efficient selection of next generation individuals instead of choosing a random set of individuals, which is predominantly followed in a standard Cuckoo Search (CS). The Patron-Prophet concept is based on a donor-acceptor concept where a donor donates information and the acceptor makes use of it. In the RCSA, the deviated information of abandoned solutions from selected solutions will be calculated and subsequently used by the newly generated solutions. A self-adaptive step size has been introduced to achieve multimodality in the RCSA. Experimental results using benchmark problems show that the RCSA performs well in terms of multimodality when compared with other existing algorithms found in the literature. This proposed RCSA is also implemented in three different engineering design problems for performance evaluation.

Optimized State Estimation of Uncertain Linear Time-Varying Complex Networks With Random Sensor Delay Subject to Uncertain Probabilities

This paper is concerned with the optimal state estimation problem for a class of time-varying uncertain dynamical networks with mixed time-delay under uncertain probabilities. Here, the mixed time-delays include the constant time-delay and the random sensor delay, where the random sensor delay is depicted by a Bernoulli distributed random variable and the occurrence probability of the random sensor delay can be uncertain. The major novelty of the paper lies in that a new time-varying state estimation algorithm is given such that, for all parameter uncertainties, mixed time-delays and uncertain probabilities, a locally optimal upper bound of the estimation error covariance is obtained and the desirable estimator parameter of easy-to-implement feature is designed. Moreover, the performance evaluation problem of the presented estimation algorithm is solved, where the monotonicity analysis is shown regarding the trace of the upper bound and the deterministic occurrence probability of random sensor delay. At last, the simulations are given to show the validity and correctness of the proposed time-varying estimation method. In particular, the comparisons are given to show the relationship of the upper bound and occurrence probability.

A Novel Class of Test Problems for Performance Evaluation of Niching Methods

This paper proposes a novel procedure for generating parametric scalable functions with diverse properties to strengthen numerical evaluation of niching methods. It combines three simple basic functions to form a composite multimodal function, in which the function parameter controls the number of global minima. The resultant composite function may show a variety of challenges in global optimization such as high condition, correlation, and presence of many undesirable local minima, as well as those peculiar to multimodal optimization, such as nonuniformly distributed global minima with dissimilar basin sizes. Moreover, the proposed procedure results in computationally inexpensive composite functions, when compared to those generated by available methods. This allows for benchmarking long-term success of niching methods on problems with many global minima. Six parametric benchmark functions are proposed in which the function parameter controls the number of global minima. Detailed analysis on distribution, basin shapes and sizes of the global minima is provided. One of the proposed test problems involve constraints, a matter which did not receive much attention in the past. These test functions are employed to compare some of the most successful niching methods in the literature. The numerical results disclose a drastic disparity between the performance of different niching methods on the composite functions and the existing test problems, demonstrating that the proposed composite functions simulate distinct challenges. Our findings highlight importance of the core search algorithm and challenge suitability of many niching strategies in more complicated landscapes and higher dimensions.

Design of Batik Crafts Industrial Performance Measurement Model in Wukirsari Region Bantul

One important factor in influencing the progress and decline of an industry is the performance factor. Performance issues are not only important for middle-to-upper-level companies and large companies, but also important for small and medium industries such as the batik craft industry in the Wukirsari region, Bantul. Given the importance of performance, researchers tried to design a performance measurement model of the batik craft industry in the Wukirsari region, Bantul with the aim of identifying performance criteria, determining performance indicators, formulating performance indicators, and making performance measurement instruments. The steps in this study are divided into four phases, namely the initial research phase and problem formulation, the design phase, the analysis phase and the conclusion phase. The initial research phase and problem formulation include, the profile of the batik craft industry in the Wukirsari region, Bantul, the current performance evaluation system, problem formulation and research objectives. The design phase includes the design process of the performance measurement model with the Balanced Scorecard method which includes setting strategic objectives, establishing performance indicators (key performance indicators), determining performance indicator formulas, making performance measurement instruments. Analysis phase includes KPI analysis and strategy map analysis. Conclusion phase includes conclusions from the results of research and suggestions for the batik craft industry in Wukirsari, Bantul. From the results of the study obtained four performance perspectives based on the balanced scorecard, namely financial, customer, internal business processes, learning and growth. five, namely: increased sales growth, high customer satisfaction, improved system and better work processes, the creation of a good work climate, and increased employee productivity.There are seven performance indicators formed, namely: the rate of sales growth, the level of customer satisfaction, level of compliance with customer complaints, percentage of defective products, number of new products, level of job satisfaction, and employee productivity. The establishment of a performance measurement worksheet, so that the performance values of each performance indicator and total performance can be known in a certain period.Keywords: Performance, Measurement, Batik

Real-time performance evaluation and improvement of assembly systems with Bernoulli machines and finite production runs

Extensive research has been investigated in the past several decades to evaluate the performance of manufacturing systems under rigid production mode. Based on the deployment of the new manufacturing strategies (e.g. smart manufacturing), real-time performance analysis, continuous improvement and efficient production management of flexible production systems are urgently to be investigated. Therefore, we study the problems of real-time performance evaluation and bottleneck of assembly systems in this paper. The system is assumed to have Bernoulli machines and finite production runs. We first derive the mathematical model of the system and then, derive the analytical formulas for performance evaluation of systems with three Bernoulli machines. In addition, we propose a decomposition and aggregation-based algorithm to approximate the system performances with high accuracy and computational efficiency. The idea is then extended to generalised assembly systems. Finally, the method of bottleneck analysis by using completion time bottleneck indicator is introduced and evaluated by numerical justification.

Fuzzy Multicriteria Analysis for Performance Evaluation of Internet-of-Things-Based Supply Chains

This paper presents a fuzzy multicriteria analysis model for evaluating the performance of Internet of Things (IoT)-based supply chains. The inherent uncertainty and imprecision of the performance evaluation process was handled by using intuitionistic fuzzy numbers. A new fuzzy multicriteria group decision making algorithm based on the technique ordered preference by similarity to the ideal solution (TOPSIS) approach, and the concept of similarity measures was developed for determining the overall performance of each alternative. The advantage of the proposed fuzzy multicriteria analysis model is that it can overcome the limitations of the existing approaches in an intuitionistic fuzzy environment. The fuzzy multicriteria group decision-making model provides organizations with the ability to evaluate the performance of their IoT-based supply chains for improving their competitiveness. An example is presented to highlight the usefulness of the proposed model for tackling a real world IoT performance evaluation problem.

GIS UHF Partial Discharge On-line Monitoring Device Evaluation

The Ultra-high Frequency (UHF) partial discharge on-line monitoring system device is widely used in gas insulated substations (GIS), and has become one of the important detection methods for partial discharge of GIS. However, due to the lack of uniform standards within the industry, the equipment produced by the manufacturers is uneven, resulting in the performance evaluation problems of the UHF online monitoring device in the purchase and acceptance process. For this question, this paper proposes a measurement method, which has two parts: UHF sensor evaluation and complete device evaluation.A set of evaluation methods was established by using a signal simulation test method and a simulated fault evaluation method, and a more comprehensive understanding of the GIS UHF partial discharge on-line monitoring device were proposed.

Study on Performance Evaluation of TEV Partial Discharge Detector

Transient Earth Voltage (TEV) detection technology has become one of the important detection methods for high voltage electrical equipment. However, due to the lack of uniform standards within the industry, the equipment manufactured by the manufacturers is not of good quality, resulting in the performance evaluation problems of the TEV partial discharge instrument during the purchase and acceptance process. Therefore, this paper proposes a signal simulation evaluation method, and analyzes in detail the advanced function evaluation of TEV partial discharge instrument including frequency characteristics, signal linearity, sensitivity, pulse count, and discharge source positioning performance. it is possible to have a more complete understanding of the performance of the TEV partial discharge meter.

Performance study of UEI based on the relatively matching of energy supply-demand information entropy

This paper studies the performance of UEI (Ubiquitous Energy Internet) by means of its energy supply-demand matching degree. First of all, the energy supply-demand matching degree of UEI is defined, and then the information entropy of energy supply-demand match degree is defined either by use of Shannon’s information entropy theory. On the basis of these two definitions, the energy matching degree information entropy of the distributed Energy Internet is defined. By the study of information entropy characteristic and energy supply-demand matching degree, the evaluation model of energy supply-demand matching degree of UEI is provided, and the performance of UEI is evaluated. Finally, the effectiveness of this evaluation model in solving the supply-demand performance evaluation problem of UEI is proved by an example.

Multicriteria Assessment of Combined Heat and Power Systems

This paper presented a multicriteria assessment model for evaluating the performance of combined heat and power systems. Interval-valued intuitionistic fuzzy numbers were used for representing the subjective and imprecise assessments of the decision maker in evaluating the relative importance of the criteria, and the performance of individual combined heat and power systems. An effective algorithm was developed based on the concept of ideal solutions for calculating the overall performance index, for each combined heat and power system across all criteria. An example was presented to demonstrate the applicability of the multicriteria assessment model, for dealing with real world combined heat and power system performance evaluation problems.

Supply chain performance evaluation using fuzzy network data envelopment analysis: a case study in automotive industry

Supply chain performance evaluation problems are evaluated using data envelopment analysis. This paper proposes a fuzzy network epsilon-based data envelopment analysis for supply chain performance evaluation. In the common data envelopment analysis models which are used for evaluation of decision-maker units efficiency, there are several inputs and outputs. One of the bugs of such models is that the intermediate products and linking activities are overlooked. Considering these intermediate activities and products, the current study evaluates the performance of decision-maker units in an automotive supply chain. There are ten decision-maker units in the supply chain in which there are three suppliers, two manufacturers, two distributors, and four customers. Moreover, the overall efficiency of input-oriented (input-based) model and input-oriented divisional efficiency are calculated. In order to improve the efficiencies, the projections onto the frontiers are obtained by using the outputs of the solved model and Lingo software. In order to show the applicability of the proposed model, it is applied on automotive industry, as a case study, to evaluate supply chain performance. Then, the overall efficiencies of DMUs and each sections (divisions) of DMUs were calculated separately. Therefore, every organization can apply this evaluation method for improving the performance of alternative factors.

Evaluation of supplier performance of high-speed train based on multi-stage multi-criteria decision-making method

In the process of developing the industry of high-speed train manufacturing (HSTM), a key problem is to evaluate the performance of suppliers by considering the special characteristics of suppliers. To address this problem, a multi-stage multi-criteria decision-making (MCDM) method is proposed based on the evidential reasoning approach. A criteria framework of the supplier performance evaluation (SPE) problem is constructed first. To describe quantitative and qualitative assessments with uncertainty, belief distributions are adopted to model the problem. Then, the rule-based information transformation technique is introduced to unify quantitative data and qualitative information. Suppose that SPE is performed at multiple stages and a decision maker may prefer the suppliers with the performance that is continuously increasing at these stages. On this assumption, stage weights are determined objectively by considering the dynamic nature of SPE at multiple stages. A real SPE problem in the HSTM enterprise located in Changzhou, Jiangsu Province, China is investigated to verify the validity and applicability of the proposed multi-stage MCDM method.

An application of network data envelopment analysis with fuzzy data for the performance evaluation in cargo sector

PurposeThe purpose of this paper is to present a methodology which enables to measure and analyze the performance of sub-process and overall system of a cargo company.Design/methodology/approachNetwork data envelopment analysis method with fuzzy data is used for performance measurement which considers the sub-process efficiency simultaneously together with the overall efficiency and also the uncertainty included in input–output data.FindingsA real-life application of the proposed model is presented for Turkey. The application results show the efficiency scores of ten branches according to each sub-process and also the overall system. Although the obtained results are case specific, the application results indicate that the inefficient branches can achieve efficiency either by decreasing circulation ratio input for human resources sub-process or by increasing closed complaint output or by decreasing open complaint output for customer relationship management sub-process.Originality/valueThe study presented provides insights into the performance measurement applications in cargo sector. The methodology presented provides the flexibility of removing or adding some new sub-processes and also decision-making units which enables the approach to be used for other performance evaluation problems.

A performance evaluation model for transportation projects based on principal component analysis

This study investigates the performance evaluation problem, which plays an important role in transport transit project supported by finance. In this paper, firstly it puts forward the evaluation indicators of transport transit project, and indicators of cause and outcome are considered; secondly, PCA (Principal Component Analysis) method is developed to take empirical researches on performance evaluation of transport transit project supported by finance. Thus, the overall development of transport transit project can be got quantitatively. At last, some important conclusions are obtained: the degree of project development is quite different; project 1 takes the leading place, while project 4 is lagging behind; project 1 fully complies with the rules and regulations, etc. Study findings and feasible suggestions are provided for academics and practitioners.

Performance Prediction and Evaluation Based on the Variability Theory in Production Lines Using ARENA Simulation

The level of performance is an important aspect of the design and control in a production line. Particularly, the level of performance of variable production line (VPL) is one of the most important influential factors in deciding production line’s flexibility. The majority of the existing solution methods for performance prediction and evaluation problems of VPL assume that the processing times, time between failures and repair times are deterministic or exponentially distributed, which could not be applied to all the problems in real cases. This paper relaxes these restrictions by proposing an ARENA simulation model for performance prediction and evaluation based on the variability theory in Factory Physics. The variable properties of time interval between product arrivals and VPL are simulated, which combining with the coefficients of variations, are presented. Through the simulation, how the variable factors influence the performance of VPL is demonstrated. The methodology in this paper can be applied to effectively predict and evaluate the performance in VPL in various production scenarios before implementing them in reality.