Fuzzy Multi-objective Decision Research Articles

Configuring a Trusted Cloud Service Model for Smart City Exploration Using Hybrid Intelligence

Emerging research concerns about the authenticated cloud service with high performance of security and assuring trust for distributed clients in a smart city. Cloud services are deployed by the third-party or web-based service providers. Thus, security and trust would be considered for every layer of cloud architecture. The principle objective of cloud service providers is to deliver better services with assurance of trust about clients' information. Cloud's users recurrently face different security challenges about the use of sharable resources. It is really difficult for Cloud Service Provider for adapting varieties of security policies to sustain their enterprises' goodwill. To make an optimistic decision that would be better suitable to provide a trusted cloud service for users' in smart city. Statistical method known as Multivariate Normal Distribution is used to select different attributes of different security entities for developing the proposed model. Finally, fuzzy multi objective decision making and Bio-Inspired Bat algorithm are applied to achieve the objective.

Fuzzy multi-objective and groups decision method in optimal selection of landslide treatment scheme

Several measures can be used to landslide control. Therefore, the optimal selection of landslide treatment scheme is a key problem in the landslide treatment design. This paper analyzed the key restricting factors of the landslide treatment scheme. Based on decision theory, fuzzy set theory, and case theory, the fuzzy multi-objective and lattice-ordered groups decision method were applied to solve the problem of optimal selection of landslide treatment schemes. Taking the Chaancun landslide treatment schemes as example, the theory of the limited feasible decision-making methods and the calculation process were determined. Results show that the fuzzy multi-objective and lattice-ordered groups decision method is feasible in the optimal selection of landslide treatment scheme, because this method can normalize the qualitative and quantitative indexes into quantitative indexes. Consequently the optimal selection result is highly objective. Therefore, this paper is significant to the comparison and optimization of landslide comprehensive treatment schemes.

Fuzzy multi-objective decision model for calibration supplier selection problem

Quality products and competitively priced services are crucial in today’s global markets. To provide quality at an acceptable price, companies seek out not only raw material and product suppliers but also calibration services suppliers. The calibration of measurement devices is one of the ISO9001 standard requirements for quality. Although companies select and manage their calibration processes as economically as possible, cost is not their only selection criterion. Technical capability, documentation competence, performance history, warranties, and communications are also considered when selecting calibration suppliers. There are numerous criteria and methods in the current literature on supplier selection, but few studies have specifically examined the selection of calibration suppliers.This paper is the first study that specifically examines the selection process for calibration suppliers by utilizing selection criteria that were researched and presented prior to this study. Due to the varied linguistic expressions of criteria and the uncertain model parameters, this paper presents a fuzzy approach for selecting a calibration supplier. The model contains relevant calibration service quality parameters such as the weight of criteria, cost, calibration time, demand, technical capability, and number of experts. This study proposes a fuzzy multi-objective linear programming model that assigns the calibration supplier to the measurement device using two objectives: maximizing the fuzzy weight of the criteria and minimizing the fuzzy calibration cost through fuzzy calibration time, the number of certified experts, the technical capability of the company, and the measurement device demand. A two-phase approach is used to solve the fuzzy multi-objective decision model. Weight, cost, and calibration time are handled as fuzzy numbers for modelling the imprecise data. In an actual application, calibration suppliers are selected for 20 measurement device types and 161 measurement devices with the fuzzy multi-objective linear programming model.

A FUZZY MULTI-OBJECTIVE MODEL AND APPLICATION FOR THE DISCRETE DYNAMIC TEMPORARY FACILITIES LOCATION PLANNING PROBLEM

The location of temporary facilities on construction sites is essential to the enhancement of productivity and safety, but it is complex due to the unique issues associated with construction. To positively contribute to the dynamic construction site layout planning field, this paper proposes a new fuzzy multi-objective decision making model. The proposed hybrid optimization model utilizes fuzzy numbers and logic to represent the closeness relationship between temporary facilities. The two main phases presented represent a specific advance in knowledge in through: (1) an opti­mization model that considers both uncertainty and dynamic elements; (2) the application of this optimization to a spe­cial project. A multi-objective simulated annealing-based genetic algorithm (MOSA-based GA) is proposed to solve the model and the case of Jinping-II hydroelectric station is studied to evaluate the model’s performance. The computational study was carried out to demonstrate the practicality and efficiency of the proposed optimization method. The study is applicable and useful to the profession.

A network behavior evaluation method for improving interactive security in virtual network worlds

ABSTRACTThe Internet is increasingly being used for socializing. In virtual network worlds (VNWs), security and trust evaluation mechanisms are weak. This study used a network behavior evaluation method to appraise the online behavior qualities and personal attributes of Internet users based on social computing. This paper first proposes a security interaction theory and factor model based on criminological theories. To understand importance of the factors affecting interactive security, we first analyze the background differences of 758 Internet users. We also design three interaction-security scales, which we use to evaluate the security values of other users. A network behavior evaluation method comprising three submethods is then developed. Finally, we present a fuzzy multiobjective decision inference (FMODI) method to integrate the three submethods to identify the optimal Internet user. There are 56 Internet users to participate in the method experiment, which include 19 valid samples regarding online entertainment, 22 samples regarding online shopping, and 15 samples regarding online social. We used quartiles to analyze these data, which we divided into four safety levels. This study provides a novel contribution to Internet safety evaluations. The security scores of the three network behavior evaluation submethods are used to warn or caution users of threats or identify users of potential threats, thereby preventing immediate damage.

Fuzzy Multi-Objective Lattice Order Decision Approach for Preference Ranking in Conflict Analysis

AbstractBased on conflict analysis and lattice order theory, this paper integrates fuzziness and non-transitivity of the preference, exclusiveness and incommensurability of the objective into conflict analysis, proposes a new fuzzy multi-objective lattice order decision method for preference ranking in conflict analysis. Furthermore, a conflict case study of Chinese enterprise overseas acquisition problem, including two players and complicated preference, is used to illustrate how the proposed method can be applied in practice along with its the feasibility and effectiveness. Conclusions showed that, compared to the traditional preference ranking in conflict analysis, the present method tends to be simpler, easier to reach an alliance and improve the stability of conflict situations. It also can avoid emotional and subjective decision-making, thus making results more rational and objective.

Tracking of experts for enhancement of activities in social network: an analysis of collaborative activity on Wikipedia by applying fuzzy logic

Experience of previous years helps in future planning and development. The profit and popularity of a social network site can only be enhanced if it can test its present state and predict its future state and then make the necessary changes. This idea was executed in this paper on a popular educational site - Wikipedia. The rate of performance of each contributor of an article was calculated by using fuzzy synthetic method. The total number of votes obtained by each contributor was the other parameter. Both the parameters, helped in calculating the rate of contribution towards an article. To check the level of authenticity of the article the total contribution rate value was compared with a standard threshold value. If the value was less than the threshold value then an expert personal was chosen to guide or enhance the standard of the article by using fuzzy multiobjective decision making technique.

风电场无功电压模糊多目标决策方法

针对风电场并网运行难以有效兼顾稳定性与经济性的问题，提出了风电场运行经济性和稳定性目标，其中经济性目标考虑风电场有功损耗指标，稳定性目标考虑风电场无功源无功裕度和风电场电压偏差两个指标。在此基础上，建立了风电场无功电压多目标优化控制模型。该模型以SVC与双馈风电机组的无功功率为控制对象，运用模糊多目标决策方法将风电场无功电压优化转换为一个多目标、多约束的非线性规划问题，并采用粒子群算法进行求解。仿真算例结果表明，所提出的优化决策方法能够实现风电场运行经济性和稳定性的双重目标，在提高风电场电压稳定性的同时，合理降低了风电场损耗。 To solve stability and economy coordinated problem caused by wind farm integration, the targets of stability and economy are put forward, in which economy target considers active power loss, and stability target includes reactive power reserve capacity and voltage deviation of wind farm. Based on this, an optimization control model of reactive power and voltage fuzzy multi-objective decision making method of wind farm is established, in which the reactive power of SVC and DFIG are taken as control objectives, and the fuzzy multi-objective decision making method is used to convert the optimization of reactive power and voltage into a multi-objective and multi-constrained nonlinear programming problem. The particle swarm algorithm (PSO) is adopted to solve the built model. The simulation example results show that the proposed method can achieve the dual targets of economy and stability of wind farms, and can improve the voltage stability of wind farms, and reasonably re-duce the power loss of wind farms.

A decision model for cost effective design of biomass based green energy supply chains

The core driver of this study is to deal with the design of anaerobic digestion based biomass to energy supply chains in a cost effective manner. In this concern, a decision model is developed. The model is based on fuzzy multi objective decision making in order to simultaneously optimize multiple economic objectives and tackle the inherent uncertainties in the parameters and decision makers’ aspiration levels for the goals. The viability of the decision model is explored with computational experiments on a real-world biomass to energy supply chain and further analyses are performed to observe the effects of different conditions. To this aim, scenario analyses are conducted to investigate the effects of energy crop utilization and operational costs on supply chain structure and performance measures.

Fuzzy Multicriteria Decision-Making: A Literature Review

Multicriteria decision-making (MCDM) refers to making decisions in the presence of multiple and usually conflicting criteria. Fuzzy decision-making is used where vague and incomplete data exist for the solution. Fuzzy multicriteria decision-making is one of the most popular problems handled by the researchers in the literature. In this paper, we survey the latest status of fuzzy multicriteria decision-making methods and classify these methods dividing into two parts: fuzzy multiattribute decision-making (MADM) and fuzzy multiobjective decision-making (MODM). Most of the publications are on fuzzy MADM since there are a plenty of classical multiattribute decision-making methods in the literature. Tabular and graphical illustrations for each method are given.

IFMOD: Intuitionistic-Based Fuzzy Multi-Objective Decision in Multi-Agent System

Multi-agent system (MAS) contains many intelligent agents, which makes decision for many practical scenarios. However, due to complex decision environment, many data required from sensors are fuzzy. Although a lot of legend solutions address this problem, the decision making result is not very accurate. To solve the problem, we present IFMOD, an algorithm using fuzzy multi-objective decision based on interval-valued intuitionistic fuzzy set. The algorithm adopts iteration way to close the precise value. To make IFMOD algorithm effectively, MAS makes hierarchical structure to complete fuzzy decision. In MAS, most intelligent agents may process the data individually, while other higher intelligent agents make a final decision entirely. The experiment shows that, it is effective for MAS to solve the problem of fuzzy decision in distributed networks.

Evaluating a green supplier selection problem using a hybrid MODM algorithm

The green supplier selection (GSS) problem is a well-known strategy to outsource with respect to environmental protection. Although different applications of GSS have been proposed in the literature, the fuzzy five-objective GSS model has not been studied yet. This paper develops a multi-objective fuzzy linear programming model for a GSS problem, including 17 criteria, formed into 5 clusters while a hybrid fuzzy multi objective decision making (MODM) is employed to solve it. The aim of this paper is to select the best set of suppliers regarding optimal allocation of order quantities while demand and supplier's capacity are restricted. In the proposed hybrid solution algorithm, fuzzy decision making trial and evaluation laboratory approach is used to understand the interrelation among criteria, and fuzzy analytical network process (ANP) provides the criteria weights with respect to their dependencies. Then, a hybrid of fuzzy ANP and fuzzy multi-objective linear programming presents optimal order allocation among the selected suppliers, verified and compared with two other methods. Finally, the conclusion and future research are presented.

Multifeature fusion for polarimetric synthetic aperture radar image classification of sea ice

Sea ice conditions are so heterogeneous, and the differences between the different ice types are less varied than that of land targets, so only using polarimetric or textural features would lead to misclassification of polarimetric synthetic aperture radar (PolSAR) data of sea ice. To support the identification of different ice types, the fusion of textural and polarimetric features would be a good solution. Simple discrimination analysis is used to rationalize a preferred features subset. Some features are analyzed, which include entropy H /alpha α /anisotropy A and three kinds of texture statistics (entropy, contrast, and correlation), in the C- and L-band polarimetric mode. After that, a multiobjective fuzzy decision model is proposed for supervised PolSAR data classification of sea ice, and the targets are categorized according to the principle of maximum membership grade. In consideration of the interference of the correlation among features, the model is based on Mahalanobis distance in which the covariances between the selected heterogeneous features could restrain the interference among redundant features. In the end, the effectiveness of the algorithm for PolSAR image classification of sea ice is demonstrated through the analysis of some experimental results.

Application of Fuzzy Multi-objective Decision Making Model for Adapted Cropping Pattern to climate change:A Case Study of Pishin River Basin of Iran

DOI: 10.6007/IJAREMS/v3-i2/900 URL: http://dx.doi.org/10.6007/IJAREMS/v3-i2/900 Abstract: Water management denotes one of the most critical problems that face the national interests in the current and near future, especially in the middle east, where, according to UNESCO, the main interstate conflicts over water occur/will occur in that region. Given that agricultural irrigation water accounts for 80% consumption of the world's water resources, better agricultural systems management can play a critical role in the peaceful resolution of such crisis. Agricultural sector of Iran on the basis of special climate and geographic position poses many challenges and problems. Among these challenges, crop selection and water management are very important. That is, to decide on the proper set of crops to be cultivated and a proper irrigation scheme. So farmers must balance conflicting objectives when planning production. Conflicts may embrace economic, environmental, cultural, social, technical, and aesthetic objectives. Selecting the best combination of management uses from numerous objectives is difficult. Fuzzy Multi-Objective Decision making (FMCD) Models provides a systematic technique for selecting alternatives that best satisfy the farmer's objectives when objectives or restrictions are not clear. Fuzzy multiple criteria decision making models generally rely on the aggregation of the objectives to form a decision function and it allows trade-off among the objectives, and has been shown to be suitable to model decision making behavior. Such decisions are made to realize a certain objectives that typically include the maximization of net profit and the minimization of required investment, minimization of water consumption. So in this research an adapted crop pattern was determined by using Fuzzy Multi- Objective decision making model.

Fuzzy goal programming for material requirements planning under uncertainty and integrity conditions

In this paper, we formulate the material requirements planning) problem of a first-tier supplier in an automobile supply chain through a fuzzy multi-objective decision model, which considers three conflictive objectives to optimise: minimisation of normal, overtime and subcontracted production costs of finished goods plus the inventory costs of finished goods, raw materials and components; minimisation of idle time; minimisation of backorder quantities. Lack of knowledge or epistemic uncertainty is considered in the demand, available and required capacity data. Integrity conditions for the main decision variables of the problem are also considered. For the solution methodology, we use a fuzzy goal programming approach where the importance of the relations among the goals is considered fuzzy instead of using a crisp definition of goal weights. For illustration purposes, an example based on modifications of real-world industrial problems is used.

Study on Distributed Power Location Optimization in Distribution Network of Power System

Network losses, cost, voltage quality need to be considered when planning the distribution network .Reasonable access of distributed power (DG) can reduce network losses and improve voltage quality. This paper establishes a distributed power siting optimization model aiming to reduce costs, network losses and improve voltage quality. Multi-objective particle swarm optimization (MOPSO) and fuzzy decision optimization technology are combined as a mean for DG siting and constant volume. Objective function is effective and reasonable through practical example.

Multi-Objective Optimizing Selection Method for Supporting Structure of Deep Foundation Excavation

According to characteristics of deep excavation, using AHP and multi-objective fuzzy decision theory and other methods to identify a suitable deep excavation bracing program preferred method of multi-objective. Combined with the specific examples of projects, using this method for the optimization of engineering support scheme selection, not only can quickly and easily determine the weight value, but also can reduce the human subjectivity of AHP, making the preferred method of science easy, better to meet the practical requirements.

Coordinated Control of EPS and ESP Based on Function Allocation and Multi-objective Fuzzy Decision

Coordinated Control of EPS and ESP Based on Function Allocation and Multi-objective Fuzzy Decision

Fuzzy multi-objective group decision making based on interval-valued intuitionistic fuzzy set

In order to improve the accuracy of data decision making,an optimization approach was proposed for the algorithm of multi-objectives group decision making.By the interval-valued intuitionistic fuzzy set theory,the optimization was approached by the method of iterative computation gradually in the situation that the part weight information was incomplete usually.Results of the simulation indicate that the algorithm has low time complexity,and can be implemented in the computer easily;moreover,it also shows the effectiveness and accuracy of the algorithm.

A multi-objective approach to supply chain visibility and risk

This paper investigates the twin effects of supply chain visibility (SCV) and supply chain risk (SCR) on supply chain performance. Operationally, SCV has been linked to the capability of sharing timely and accurate information on exogenous demand, quantity and location of inventory, transport related cost, and other logistics activities throughout an entire supply chain. Similarly, SCR can be viewed as the likelihood that an adverse event has occurred during a certain epoch within a supply chain and the associated consequences of that event which affects supply chain performance. Given the multi-faceted attributes of the decision making process which involves many stages, objectives, and stakeholders, it beckons research into this aspect of the supply chain to utilize a fuzzy multi-objective decision making approach to model SCV and SCR from an operational perspective. Hence, our model incorporates the objectives of SCV maximization, SCR minimization, and cost minimization under the constraints of budget, customer demand, production capacity, and supply availability. A numerical example is used to demonstrate the applicability of the model. Our results suggest that decision makers tend to mitigate SCR first then enhance SCV.