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Journal articles on the topic 'Fuzzy trade'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Liu, Yang. "Foreign Trade Export Forecast Based on Fuzzy Neural Network." Complexity 2021 (June 11, 2021): 1–10. http://dx.doi.org/10.1155/2021/5523222.

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This article first analyzes the significance and methods of foreign trade export forecasting and determines the index system of foreign trade export forecasting by analyzing the results of foreign trade export forecasting research at home and abroad. Subsequently, the related concepts and principles of artificial neural network and fuzzy theory are explained, the types and training algorithms of the fuzzy neural network are introduced, and the neural network and fuzzy theory are combined to establish the prediction model. Finally, according to the characteristics of foreign trade exports, this article comprehensively considers the influence of various factors, applies the fuzzy neural network model to the foreign trade export forecast, introduces the whole process of the establishment of the fuzzy neural network forecasting model in detail, and predicts the change interval of foreign trade exports.

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Sani, Mohammadreza Rafiee, and Mohammadreza Alirezaee. "Fuzzy trade-offs in data envelopment analysis." International Journal of Operational Research 30, no. 4 (2017): 540. http://dx.doi.org/10.1504/ijor.2017.087828.

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Rafiee Sani, Mohammadreza, and Mohammadreza Alirezaee. "Fuzzy trade-offs in data envelopment analysis." International Journal of Operational Research 30, no. 4 (2017): 540. http://dx.doi.org/10.1504/ijor.2017.10008474.

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4

Shah, Nita H., Sarla Pareek, and Isha Sangal. "EOQ in fuzzy environment and trade credit." international journal of industrial engineering computations 3, no. 2 (January 1, 2012): 133–44. http://dx.doi.org/10.5267/j.ijiec.2011.07.001.

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5

Sishi, Qin, Tang Ji’an, Liu Feng, Shao Shuqian, and Lu Shiying. "Research and Practice of Quantitative Models on The Freedom of Trade Based on AHP-FCE Method: Taking Major Countries in WTO as Examples." E3S Web of Conferences 214 (2020): 01048. http://dx.doi.org/10.1051/e3sconf/202021401048.

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In recent years, protectionism and unilateralism in the field of international trade are increasing. The WTO-centric multilateral trade regime has been hit. By researching the index of trade freedom among countries in international trade, this paper takes five important countries in WTO as an example, and constructs the trade freedom index and the national trade freedom model. The study reviewed and analysed global and regional developments in cross-border trade and investigated five varialbes that impacted the index of trade freedom. Then the fuzzy comprehensive analysis method (FCE) is used to obtain the comprehensive evaluation matrix by fuzzy arithmetic processing through the evaluation index weight and fuzzy relation matrix. Therefore, the changing data of the index of trade freedom in five countries from 2017 to 2018 are obtained. It is discovered that there is a significant difference in the index of trade freedom among countries. What’s worse, the average of the global index has declined year by year. This phenomenon is caused by the decline of global trade volume and the prevalence of new trade barriers. In the end, this paper proposes the implementation of multilateral negotiations and the establishment of long-term penalties as possible solutions.

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Monreal-Pérez, Joaquín, and Valeska V. Geldres-Weiss. "A configurational approach to the impact of trade fairs and trade missions on firm export activity." BRQ Business Research Quarterly 23, no. 1 (January 2020): 234094442090104. http://dx.doi.org/10.1177/2340944420901045.

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Export promotion programmes (EPPs) are argued to support firms’ export activity. However, the empirical evidence for the link between EPPs and exporting is inconclusive. We argue and demonstrate by using fuzzy set methods one can uncover configurations that combine the firm’s participation in specific EPPs, namely trade missions and fairs, together with certain firm-specific characteristics. We base our analysis on a sample of 641 Chilean exporters (2010-2015), and show regression results are mostly insignificant and with a much lower model fit level compared with our fuzzy set analysis. Our main findings illustrate that small, young and non-export-experienced firms gain the most from trade fairs and trade missions, which supports the notion that EPPs provide the information required in export markets. JEL CLASSIFICATION M160; M380; C120

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Ansari, Azarnoush, and Arash Riasi. "Customer Clustering Using a Combination of Fuzzy C-Means and Genetic Algorithms." International Journal of Business and Management 11, no. 7 (June 21, 2016): 59. http://dx.doi.org/10.5539/ijbm.v11n7p59.

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<p>This study intends to combine the fuzzy c-means clustering and genetic algorithms to cluster the customers of steel industry. The customers were divided into two clusters by using the variables of the LRFM (length, recency, frequency, monetary value) model. Results indicated that customers belonging to the first cluster had a higher length of the relationship, recency of trade, and frequency of trade but lower monetary value compared to the average values of these criteria for all customers. The results also showed that customers belonging to the second<br />cluster had a higher recency of trade and monetary value but lower length of the relationship and frequency of trade compared to the average values of these criteria for all customers. It was also found that the combined algorithm (i.e., fuzzy c-means clustering and genetic algorithm) used in this study had a lower mean squared error (MSE) compared to fuzzy c-means clustering.</p>

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Gedeon, Tamás D., László T. Kóczy, and Alessandro Zorat. "Optimal Size Fuzzy Models." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 3 (March 20, 2007): 335–41. http://dx.doi.org/10.20965/jaciii.2007.p0335.

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Approximate models using fuzzy rule bases can be made more precise by suitably increasing the size of the rule base and decreasing uncertainty in the rules. A large rule base, however, requires more time for its evaluation and hence the problem arises of determining the size that is good enough for the task at hand, but allows as fast as possible reasoning using the rule base. This trade-off between computation time and precision is significant whenever a prediction is made which can become “out of date” or “too old” if not used in time. The trade off is considered here in the context of tracking a moving target. In this problem, a higher degree of accuracy results in tighter precision of determining target location, but at the cost of longer computation time, during which the target can move further away, thus ultimately requiring a longer search for exact target localisation. This paper examines the problem of determining the optimal rule base size that will yield a minimum total time required to repeatedly re-acquire the moving target, as done by a cat that plays with a mouse. While this problem has no known solution in its general formulation, solutions are shown here for specific contexts.

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9

Weihua Xu. "Fuzzy models for integrated inventory problem under trade credit." Journal of Convergence Information Technology 7, no. 10 (June 30, 2012): 21–33. http://dx.doi.org/10.4156/jcit.vol7.issue10.3.

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10

Lee, Jonathan, and Jong-Yih Kuo. "Fuzzy decision making through trade-off analysis between criteria." Information Sciences 107, no. 1-4 (June 1998): 107–26. http://dx.doi.org/10.1016/s0020-0255(97)10020-2.

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11

Ke, Hua, Weimin Ma, Xin Gao, and Weihua Xu. "New fuzzy models for time-cost trade-off problem." Fuzzy Optimization and Decision Making 9, no. 2 (March 24, 2010): 219–31. http://dx.doi.org/10.1007/s10700-010-9076-z.

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12

Keshavarz, Esmaeil, and Abbas Shoul. "Project Time-Cost-Quality Trade-off Problem: A Novel Approach Based on Fuzzy Decision Making." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 28, no. 04 (August 2020): 545–67. http://dx.doi.org/10.1142/s0218488520500233.

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Trade-off problems concentrate on balancing the main parameters of a project as completion time, total cost and quality of activities. In this study, the problem of project time-cost-quality trade-off is formulated and solved from a new standpoint. For this purpose, completion time and crash cost of project are illustrated as fuzzy goals, also the dependency of implementing time of each activity and its execution-quality is described by a fuzzy number. The overall quality of the project execution is defined as the minimum execution-quality of the project activities that should be maximized. Based on some real assumptions, a three-objective programming problem associated with the time-cost-quality trade-off problem is formulated; then with the aim of identifying a fair and appropriate trade-off, the research problem is reformulated as a single objective linear programming by utilizing a fuzzy decision-making methodology. Generating a final preferred solution, rather than a set of Pareto optimal solutions, and having a reasonable interpretation are two most important advantages of the proposed approach. To explain the practical performance of the proposed models and approach, a time-cost-quality trade-off problem for a project with real data is solved and analyzed.

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Holmes, M. S., and Asok Ray. "Fuzzy Damage Mitigating Control of Mechanical Structures." Journal of Dynamic Systems, Measurement, and Control 120, no. 2 (June 1, 1998): 249–56. http://dx.doi.org/10.1115/1.2802416.

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This paper presents the architecture and synthesis of a damage mitigating control system for mechanical structures where the objective is to achieve high performance with increased reliability, availability, component durability, and maintainability. The proposed control system has a two-tier structure. In the lower tier a linear sampled-data controller tracks a reference trajectory vector while the upper tier contains a fuzzy-logic-based damage controller which makes a trade-off between system performance and the damage in critical components. The synthesis procedure is demonstrated by simulation experiments on the model of a reusable rocket engine. The simulation results explore the feasibility of automatically regulating the damage/performance trade-off in a real-time setting.

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Acharjya, Biswajit, and Subhashree Natarajan. "A Fuzzy Rough Feature Selection Framework for Investors Behavior Towards Gold Exchange-Traded Fund." International Journal of Business Analytics 6, no. 2 (April 2019): 46–73. http://dx.doi.org/10.4018/ijban.2019040103.

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Behavioural finance has gained research interest among researchers because of investor behavior and market anomalies. Investor behaviour varies with demographics and geographic characteristics. Further, investor behavior towards a gold exchange trade fund is gaining research interest due to various factors. Not much research has been carried out in this direction, with the exception of some comparisons. Therefore, the performance of a gold exchange traded fund needs to be assessed from the investor behavior perspective. Additionally, the investors behavior contains uncertainties. Thus, there is a need for intelligent techniques for identifying the investors behavior despite the presence of uncertain behavioral characteristics. Therefore, to study uncertain behavior characteristic in gold exchange traded fund, in this article the authors employ a fuzzy rough set. They employ fuzzy rough quick reduct algorithm to find the superfluous attributes. Further decision rules are generated to identify the chief feature of investors' behavior towards gold exchange traded fund.

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15

RUBINSON, TERESA. "MULTI-PERIOD RISK MANAGEMENT USING FUZZY LOGIC." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 04, no. 05 (October 1996): 449–66. http://dx.doi.org/10.1142/s0218488596000263.

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In this paper, we present a fuzzy dynamic programming procedure for long term risk management. This approach is designed to provide insights on trade-offs between potential risks and rewards, the dynamics of interacting economic factors, and the feasibility of corporate goals over a long term planning horizon. This approach is applicable to many long term planning problems involving selection from a number of alternatives, when the decision parameters are imprecise and absolute requirements and decision thresholds can not be specified. A few examples of problems of this type include: portfolio optimization, risk management, evaluation of securities, liquidity management, and asset/liability management (which is given particular emphasis in this paper). Our formulation provides a computationally efficient and natural representation of the decision trade-offs inherent in many long term money management problems. This, in turn, facilitates the exploration and analysis of many alternative investment strategies under many possible future scenarios.

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Wang, Ji Gan, Yong Chen, Ting Li, and Shu Shu Huang. "Study on Fuzzy Recognition Model of Carbon Emission Rights Pricing." Advanced Materials Research 807-809 (September 2013): 852–56. http://dx.doi.org/10.4028/www.scientific.net/amr.807-809.852.

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Complying with the situation of ecological civilization construction in our country, carbon trade is the inevitable trend of world economic development. The core of the carbon trade is the pricing of the carbon emission rights. The pricing process of carbon emission rights is ambiguity, uncertainty and complexity, so it is more reasonable and scientific to put forward the carbon emission rights pricing model by combining the fuzzy recognition model with the highest price and the lowest price of carbon emission rights price. Then, the model is applied to predict the price of China's carbon emission in 2014 year. The result shows that the price is consistent with the forecasting prices of the international carbon trade market in the same point, which can provide some reference to the setting of the pricing of domestic carbon emission quotas in secondary market in the future.

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17

Xu, Weihua. "Integrated inventory problem under trade credit in fuzzy random environment." Fuzzy Optimization and Decision Making 13, no. 3 (February 6, 2014): 329–44. http://dx.doi.org/10.1007/s10700-014-9177-1.

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18

Ke, Hua, and Junjie Ma. "Modeling project time–cost trade-off in fuzzy random environment." Applied Soft Computing 19 (June 2014): 80–85. http://dx.doi.org/10.1016/j.asoc.2014.01.040.

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19

GUPTA, PANKAJ, SHILPI VERMA, and MUKESH KUMAR MEHLAWAT. "A MEMBERSHIP FUNCTION APPROACH FOR COST-RELIABILITY TRADE-OFF OF COTS SELECTION IN FUZZY ENVIRONMENT." International Journal of Reliability, Quality and Safety Engineering 18, no. 06 (December 2011): 573–95. http://dx.doi.org/10.1142/s0218539311004251.

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The optimization techniques used in commercial-off-the-shelf (COTS) selection process faces challenges to deal with uncertainty in many important selection parameters, for example, cost, reliability and delivery time. In this paper, we propose a fuzzy optimization model for selecting the best COTS product among the available alternatives for each module in the development of modular software systems. The proposed model minimizes the total cost of the software system satisfying the constraints of minimum threshold on system reliability, maximum threshold on the delivery time of the software, and incompatibility among COTS products. In order to deal with uncertainty in real-world applications of COTS selection, the coefficients of the cost objective function, delivery time constraints and minimum threshold on reliability are considered fuzzy numbers. The fuzzy optimization model is converted into a pair of mathematical programming problems parameterized by possibility (feasibility) level α using Zadeh's extension principle. The solutions of the resultant problems at different α-cuts provide lower and upper bounds of the fuzzy minimum total cost which helps in constructing the membership function of the cost objective function. The solution approach provide fuzzy solutions instead of a single crisp solution thereby giving decision maker enough flexibility in maintaining cost-reliability trade-off of COTS selection besides meeting other important system requirements. A real-world case study is discussed to demonstrate the effectiveness of the proposed model in fuzzy environment.

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Zhai, Jun, Jian Feng Li, and Yan Chen. "Knowledge Modeling of Product Data Based on Fuzzy Ontology." Applied Mechanics and Materials 26-28 (June 2010): 347–51. http://dx.doi.org/10.4028/www.scientific.net/amm.26-28.347.

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Ontology is the basis of knowledge modeling on the Semantic Web, and fuzzy ontology is an extension of domain ontology for solving the uncertainty problems. Ontology-base knowledge modeling of product data management (PDM) is meaningful for product design and trade etc. In order to handle fuzzy phenomenon and uncertainty of product knowledge, this paper proposes a series of fuzzy ontology models that consists of fuzzy domain ontology and fuzzy linguistic variable ontologies. Then, a fuzzy ontology framework is presented, including three parts: concepts, properties of concepts and values of properties. The application, which uses fuzzy ontology to model product knowledge, shows that these models can overcome the localization of other fuzzy ontology models, and this research facilitates the fuzzy knowledge sharing and reuse for PDM on the Semantic Web.

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Martino, Ferdinando Di, and Salvatore Sessa. "A New Validity Index Based on Fuzzy Energy and Fuzzy Entropy Measures in Fuzzy Clustering Problems." Entropy 22, no. 11 (October 23, 2020): 1200. http://dx.doi.org/10.3390/e22111200.

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Two well-known drawbacks in fuzzy clustering are the requirement of assigning in advance the number of clusters and random initialization of cluster centers. The quality of the final fuzzy clusters depends heavily on the initial choice of the number of clusters and the initialization of the clusters, then, it is necessary to apply a validity index to measure the compactness and the separability of the final clusters and run the clustering algorithm several times. We propose a new fuzzy C-means algorithm in which a validity index based on the concepts of maximum fuzzy energy and minimum fuzzy entropy is applied to initialize the cluster centers and to find the optimal number of clusters and initial cluster centers in order to obtain a good clustering quality, without increasing time consumption. We test our algorithm on UCI (University of California at Irvine) machine learning classification datasets comparing the results with the ones obtained by using well-known validity indices and variations of fuzzy C-means by using optimization algorithms in the initialization phase. The comparison results show that our algorithm represents an optimal trade-off between the quality of clustering and the time consumption.

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Lai, E., S. Lundie, and N. J. Ashbolt. "A new approach to aid urban water management decision making using trade-off sacrifice modelled by fuzzy logic." Water Science and Technology 56, no. 8 (October 1, 2007): 11–20. http://dx.doi.org/10.2166/wst.2007.597.

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An approach to aid decision making for urban water management is presented that is based on the concept of trade-off sacrifice level in pairwise comparisons between criteria, modelled using fuzzy logic. This approach is illustrated by a case study – selection of alternative water supplies for a Sydney household. Four key decision making criteria covering health, economic, environment and technical aspects are selected: annual probability of infection, life cycle energy use, life cycle cost and reliability. The decision making problem is to select between cases with different volume and application of recycled greywater and rainwater in light of the four criteria. Decision maker's preference is expressed by five levels of trade-off sacrifice between pairs of criteria. The decision makers can assign their preferences for sacrifice level by linguistic assessment and the output trade-off weight (TOW). Measures of decision makers' perceived trade-off level are modelled by a rule-based fuzzy logic control system. The final analysis shows the performance for each sacrifice class for each case, to aid overall decision making with stakeholders.

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REY, M. ISABEL, MARTA GALENDE, M. J. FUENTE, and GREGORIO I. SAINZ-PALMERO. "CHECKING ORTHOGONAL TRANSFORMATIONS AND GENETIC ALGORITHMS FOR SELECTION OF FUZZY RULES BASED ON INTERPRETABILITY-ACCURACY CONCEPTS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 20, supp02 (September 11, 2012): 159–86. http://dx.doi.org/10.1142/s0218488512400193.

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Fuzzy modeling is one of the most known and used techniques in different areas to model the behavior of systems and processes. In most cases, as in data-driven fuzzy modeling, these fuzzy models reach a high performance from the point of view of accuracy, but from other points of view, such as complexity or interpretability, they can present a poor performance. Several approaches are found in the bibliography to reduce the complexity and improve the interpretability of the fuzzy models. In this paper, a post-processing approach is carried out via rule selection, whose aim is to choose the most relevant rules for working together on the well-known accuracy-interpretability trade-off. The rule relevancy is based on Orthogonal Transformations, such as the SVD-QR rank revealing approach, the P-QR and OLS transformations. Rule selection is carried out using a genetic algorithm that takes into account the information obtained by the Orthogonal Transformations. The main objective is to check the true significance, drawbacks and advantages of the rule selection based on the orthogonal transformations via the rule firing strength matrix. In order to carry out this aim, a neuro-fuzzy system, FasArt (Fuzzy Adaptive System ART based), and several case studies, data sets from the KEEL Project Repository, are used to tune and check this selection of rules based on orthogonal transformations, genetic selection and accuracy-interpretability trade-off. This neuro-fuzzy system generates Mamdani fuzzy rule based systems (FRBSs), in an approximative way. NSGA-II is the MOEA tool used to tune the proposed rule selection.

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24

Nariman Zadeh, Nader, and Amir Hajiloo. "Pareto Optimal Robust Design of Fuzzy Fractional-Order Pid Controllers." Advanced Materials Research 403-408 (November 2011): 4735–42. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.4735.

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In this paper, a multi-objective uniform-diversity genetic algorithm (MUGA) is used for Pareto optimum design of fuzzy fractional-order PID controllers for plants with parametric uncertainties. Two conflicting objective functions have been used in Pareto design of the fuzzy fractional-order PID controller. The results clearly show that an effective trade-off can be compromisingly achieved among the different fuzzy fractional-order PID controllers obtained using the methodology of this work and to achieve a robust design against the plant’s uncertainties.

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Yu, Guo, Weijian Li, and Xiaobo Zhou. "An realistic study on the assessment system of international competitiveness of service trade using fuzzy-analytic network process." Journal of Intelligent & Fuzzy Systems 40, no. 4 (April 12, 2021): 8197–206. http://dx.doi.org/10.3233/jifs-189642.

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The Belt and Road (abbreviated as B&R) creates opportunities for the economy and trade development and the improvement of national relations of the Belt and Road countries. Development of service trade plays an important role in the Belt and Road. Henan Province takes the opportunity of B&R to develop the international service industry and makes some achievements. In the new era of development, analyzing the trade competitiveness of international service in Henan Province under the background of the Belt and Road is of great significance to help Henan Province recognize its own strengths and weaknesses in service trade development and make targeted improvements. Studies have shown that the share of international market, revealed, advantages of comparative competitiveness trade and service trade openness of service trade in Henan Province under the background of the Belt and Road are constantly improving, but the overall development level is still low and slow development occurs. We utilize the concept of fuzzy embedded along with Analytic Network Process (ANP) which makes it suitable for managing vagueness of the linguistics information of assessment system. Therefore, in order to further improve the international competitiveness of service trade in Henan Province, it is necessary to optimize the international market share, competitiveness, and degree of openness. Specifically, it is necessary to transform and upgrade the traditional service trade industry, continue to expand the breadth and depth of service trade openness, strengthen the talent team building to improve the quality of employees, and promote the brand construction of service industry to enhance the industry’s development potential.

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26

Dwivedi, Praveen Kumar, and Surya Prakash Tripathi. "A Review of Multi-Objective Evolutionary Based Fuzzy Classifiers." Recent Advances in Computer Science and Communications 13, no. 1 (March 13, 2020): 77–85. http://dx.doi.org/10.2174/2213275912666190410142052.

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Background: Fuzzy systems are employed in several fields like data processing, regression, pattern recognition, classification and management as a result of their characteristic of handling uncertainty and explaining the feature of the advanced system while not involving a particular mathematical model. Fuzzy rule-based systems (FRBS) or fuzzy rule-based classifiers (mainly designed for classification purpose) are primarily the fuzzy systems that consist of a group of fuzzy logical rules and these FRBS are unit annexes of ancient rule-based systems, containing the "If-then" rules. During the design of any fuzzy systems, there are two main objectives, interpretability and accuracy, which are conflicting with each another, i.e., improvement in any of those two options causes the decrement in another. This condition is termed as Interpretability –Accuracy Trade-off. To handle this condition, Multi-Objective Evolutionary Algorithms (MOEA) are often applied within the design of fuzzy systems. This paper reviews the approaches to the problem of developing fuzzy systems victimization evolutionary process Multi-Objective Optimization (EMO) algorithms considering ‘Interpretability-Accuracy Trade-off, current research trends and improvement in the design of fuzzy classifier using MOEA in the future scope of authors. Methods: The state-of-the-art review has been conducted for various fuzzy classifier designs, and their optimization is reviewed in terms of multi-objective. Results: This article reviews the different Multi-Objective Optimization (EMO) algorithms in the context of Interpretability -Accuracy tradeoff during fuzzy classification. Conclusion: The evolutionary multi-objective algorithms are being deployed in the development of fuzzy systems. Improvement in the design using these algorithms include issues like higher spatiality, exponentially inhabited solution, I-A tradeoff, interpretability quantification, and describing the ability of the system of the fuzzy domain, etc. The focus of the authors in future is to find out the best evolutionary algorithm of multi-objective nature with efficiency and robustness, which will be applicable for developing the optimized fuzzy system with more accuracy and higher interpretability. More concentration will be on the creation of new metrics or parameters for the measurement of interpretability of fuzzy systems and new processes or methods of EMO for handling I-A tradeoff.

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Noh, Jiseong, Jong Soo Kim, and Seung-June Hwang. "A Multi-Item Replenishment Problem with Carbon Cap-and-Trade under Uncertainty." Sustainability 12, no. 12 (June 15, 2020): 4877. http://dx.doi.org/10.3390/su12124877.

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Recently, as global warming has become a major issue, many companies have increased their efforts to control carbon emissions in green supply chain management (GSCM) activities. This paper deals with the multi-item replenishment problem in GSCM, from both economic and environmental perspectives. A single buyer orders multiple items from a single supplier, and simultaneously considers carbon cap-and-trade under limited storage capacity and limited budget. In this case we can apply a can-order policy, which is a well-known multi-item replenishment policy. Depending on the market characteristics, we develop two mixed-integer programming (MIP) models based on the can-order policy. The deterministic model considers a monopoly market in which a company fully knows the market information, such that both storage capacity and budget are already determined. In contrast, the fuzzy model considers a competitive or a new market, in which case both of those resources are considered as fuzzy numbers. We performed numerical experiments to validate and assess the efficiency of the developed models. The results of the experiments showed that the proposed can-order policy performed far better than the traditional can-order policy in GSCM. In addition, we verified that the fuzzy model can cope with uncertainties better than the deterministic model in terms of total expected costs.

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Alzarrad, M. Ammar, Gary P. Moynihan, Muhammad T. Hatamleh, and Siyuan Song. "Fuzzy Multicriteria Decision-Making Model for Time-Cost-Risk Trade-Off Optimization in Construction Projects." Advances in Civil Engineering 2019 (November 27, 2019): 1–7. http://dx.doi.org/10.1155/2019/7852301.

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As is often the case in project scheduling, when the project duration is shortened to decrease total cost, the total float is lost resulting in added critical or nearly critical activities. This, in turn, results in decreasing the probability of completing the project on time and increases the risk of schedule delays. To solve this problem, this research developed a fuzzy multicriteria decision-making (FMCDM) model. The objective of this model is to help project managers improve their decisions regarding time-cost-risk trade-offs (TCRTO) in construction projects. In this model, an optimization algorithm based on fuzzy logic and analytic hierarchy process (AHP) has been used to analyze the time-cost-risk trade-off alternatives and select the best one based on selected criteria. The algorithm was implemented in the MATLAB software and applied to two case studies to verify and validate the presented model. The presented FMCDM model could help produce a more reliable schedule and mitigate the risk of projects running overbudget or behind schedule. Further, this model is a powerful decision-making instrument to help managers reduce uncertainties and improve the accuracy of time-cost-risk trade-offs. The presented FMCDM model employed fuzzy linguistic terms, which provide decision-makers with the opportunity to give their judgments as intervals comparing to fixed value judgments. In conclusion, the presented FMCDM model has high robustness, and it is an attractive alternative to the traditional methods to solve the time-cost-risk trade-off problem in construction.

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Jaini, Nor, and Sergey Utyuzhnikov. "A Fuzzy Trade-Off Ranking Method for Multi-Criteria Decision-Making." Axioms 7, no. 1 (December 26, 2017): 1. http://dx.doi.org/10.3390/axioms7010001.

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30

Boggero, Luca, Marco Fioriti, Carlo Stefano Ragusa, and Sabrina Corpino. "Trade off studies of hybrid-electric aircraft by Fuzzy Logic methodology." International Journal of Applied Electromagnetics and Mechanics 56 (February 14, 2018): 143–52. http://dx.doi.org/10.3233/jae-172293.

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31

Eshtehardian, Ehsan, Abbas Afshar, and Reza Abbasnia. "Fuzzy-based MOGA approach to stochastic time–cost trade-off problem." Automation in Construction 18, no. 5 (August 2009): 692–701. http://dx.doi.org/10.1016/j.autcon.2009.02.001.

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32

Nun, Sophanna, Dominic Chwan Yee Foo, Raymond R. Tan, Luis F. Razon, and Ryuichi Egashira. "Fuzzy automated targeting for trade-off analysis in batch water networks." Asia-Pacific Journal of Chemical Engineering 6, no. 3 (April 4, 2011): 537–51. http://dx.doi.org/10.1002/apj.572.

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33

Zhou, Wei, and Zeshui Xu. "Score-hesitation trade-off and portfolio selection under intuitionistic fuzzy environment." International Journal of Intelligent Systems 34, no. 2 (October 11, 2018): 325–41. http://dx.doi.org/10.1002/int.22052.

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Baranyi, Péter, Péter Korondi, Ron J. Patton, and Hideki Hashimoto. "TRADE-OFF BETWEEN APPROXIMATION ACCURACY AND COMPLEXITY FOR TS FUZZY MODELS." Asian Journal of Control 6, no. 1 (October 22, 2008): 21–33. http://dx.doi.org/10.1111/j.1934-6093.2004.tb00181.x.

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Yadav, Dharmendra, S. R. Singh, and Rachna Kumari. "Retailer's optimal policy under inflation in fuzzy environment with trade credit." International Journal of Systems Science 46, no. 4 (June 6, 2013): 754–62. http://dx.doi.org/10.1080/00207721.2013.801094.

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Lin, Ling-Zhong. "A perceptual measure of trade shows using fuzzy quality deployment development." Expert Systems with Applications 37, no. 5 (May 2010): 3921–33. http://dx.doi.org/10.1016/j.eswa.2009.11.025.

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Chen, Shih-Pin, and Ming-Jiun Tsai. "Time–cost trade-off analysis of project networks in fuzzy environments." European Journal of Operational Research 212, no. 2 (July 2011): 386–97. http://dx.doi.org/10.1016/j.ejor.2011.02.002.

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Nishizaki, Ichiro, and Fumiko Seo. "Interactive support for fuzzy trade-off evaluation in group decision making." Fuzzy Sets and Systems 68, no. 3 (December 1994): 309–25. http://dx.doi.org/10.1016/0165-0114(94)90186-4.

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39

Gorzałczany, M. B., and F. Rudziński. "Handling fuzzy systems’ accuracy-interpretability trade-off by means of multi-objective evolutionary optimization methods – selected problems." Bulletin of the Polish Academy of Sciences Technical Sciences 63, no. 3 (September 1, 2015): 791–98. http://dx.doi.org/10.1515/bpasts-2015-0090.

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Abstract The paper addresses several open problems regarding the automatic design of fuzzy rule-based systems (FRBSs) from data using multi-objective evolutionary optimization algorithms (MOEOAs). In particular, we propose: a) new complexity-related interpretability measure, b) efficient strong-fuzzy-partition implementation for improving semantics-related interpretability, c) special-coding-free implementation of rule base and original genetic operators for its processing, and d) implementation of our ideas in the context of well-known MOEOAs such as SPEA2 and NSGA-II. The experiments demonstrate that our approach is an effective tool for handling FRBSs’ accuracy-interpretability trade-off, i.e, designing FRBSs characterized by various levels of such a trade-off (in particular, for designing highly interpretability-oriented systems of still competitive accuracy).

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HONG, TZUNG-PEI, CHAN-SHENG KUO, and SHENG-CHAI CHI. "TRADE-OFF BETWEEN COMPUTATION TIME AND NUMBER OF RULES FOR FUZZY MINING FROM QUANTITATIVE DATA." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 09, no. 05 (October 2001): 587–604. http://dx.doi.org/10.1142/s0218488501001071.

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Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. Most conventional data-mining algorithms identify the relationships among transactions using binary values. Transactions with quantitative values are however commonly seen in real-world applications. We proposed a fuzzy mining algorithm by which each attribute used only the linguistic term with the maximum cardinality int he mining process. The number of items was thus the same as that of the original attributes, making the processing time reduced. The fuzzy association rules derived in this way are not complete. This paper thus modifies it and proposes a new fuzzy data-mining algorithm for extrating interesting knowledge from transactions stored as quantitative values. The proposed algorithm can derive a more complete set of rules but with more computation time than the method proposed. Trade-off thus exists between the computation time and the completeness of rules. Choosing an appropriate learning method thus depends on the requirement of the application domains.

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Tsao, Yu-Chung, Erzanda Nugraha Ridhwan Amir, Vo-Van Thanh, and M. Dachyar. "Designing an eco-efficient supply chain network considering carbon trade and trade-credit: A robust fuzzy optimization approach." Computers & Industrial Engineering 160 (October 2021): 107595. http://dx.doi.org/10.1016/j.cie.2021.107595.

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YEN, JOHN, and XIAOQING LIU. "APPROXIMATE REASONING ABOUT PRIORITIES OF IMPRECISE CONFLICTING REQUIREMENTS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 03, no. 02 (June 1995): 143–62. http://dx.doi.org/10.1142/s0218488595000128.

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Elasticity in an imprecise requirement needs to be captured to enable the trade-off analysis of conflicting requirements. One of the most important issues in the trade-off analysis of conflicting requirements is to understand their priorities. Requirement analysts need to know not only the relative ordering of requirements based on their importance but also how much a requirement is more important than another requirement in order to achieve an effective trade-off between conflicting requirements. Existing formal methods for requirement engineering are limited in addressing these issues. This paper presents a formal methodology for reasoning about their priority by analyzing the customer’s trade-off preference among imprecise conflicting requirements. The elasticity in imprecise requirements is captured using fuzzy logic. Conflicting and cooperative relationships are classified to detect the conflicts between requirements. Multiple requirements are combined based fuzzy multi-criteria decision making techniques. We have also developed a possibilistic reasoning framework for inferring the lower bound of relative priority from case analysis. Consistency and nonredundancy criteria are established to facilitate the aggregation of possibilistic statement on the lower bounds of relative priority. Finally, we describe a process for transforming the lower bounds of relative priority into weights of importance so that they can be used in the aggregation of conflicting requirements to resolve conflicts.

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Chaudhury, Rahul, and Sahidul Islam. "A Multi-Objective Risk Return Trade off Models for Banks: Fuzzy Programming Approach." Mathematical Modelling of Engineering Problems 8, no. 2 (April 28, 2021): 179–88. http://dx.doi.org/10.18280/mmep.080203.

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The main focus of banking sector is on the risk management. Asset liability management (ALM) is one of the key processes to manage the risks. The objective of this paper is to develop a multi-objective asset liability optimization model for banks with the maximization of market value of equity and minimization of duration gap as the objective function. Several liquidity ratios, concept of duration and convexity are considered to manage the risk properly. Interest rate risk and liquidity risk are two major considerations in both the regulation and management of a bank. As we know that, with the fluctuation of the market interest rate, the market value of assets and liabilities of a bank changes and that affects a change in owner’s equity. In order to overcome such type of situation here we will use the concept of duration and convexity to manage the interest rate risk. In case of liquidity risk the shortage of liquidity may also put that bank in risk and simultaneously it is very crucial to manage the cash flow properly. So here we will use some major liquidity ratios to manage the liquidity risk. We will take the help of fuzzy programming technique to solve our model properly. A numerical example is given to illustrate our model by considering a hypothetical bank balance sheet. Also we will compare the result obtained by fuzzy technique with result obtained by a non fuzzy based technique.

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Xu, Jixiang, Yanhua Tan, Jinggui Gao, and Enmin Feng. "Pricing Currency Option Based on the Extension Principle and Defuzzification via Weighting Parameter Identification." Journal of Applied Mathematics 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/623945.

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We present a fuzzy version of the Garman-Kohlhagen (FG-K) formula for pricing European currency option based on the extension principle. In order to keep consistent with the real market, we assume that the interest rate, the spot exchange rate, and the volatility are fuzzy numbers in the FG-K formula. The conditions of a basic proposition about the fuzzy-valued functions of fuzzy subsets are modified. Based on the modified conditions and the extension principle, we prove that the fuzzy price obtained from the FG-K formula for European currency option is a fuzzy number. To simplify the trade, the weighted possibilistic mean (WPM) value with a weighting function is adopted to defuzzify the fuzzy price to a crisp price. The numerical example shows our method makes theα-level set of fuzzy price smaller, which decreases the fuzziness. The example also indicates that the WPM value has different approximation effects to real market price by taking different values of weighting parameter in the weighting function. Inspired by this example, we provide a method, which can identify the optimal parameter.

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Shen, Yun Cheng, Hong Zhang, and Xu Liang Duan. "Trust Model of P2P Network Based on Fuzzy Degree of Credit." Applied Mechanics and Materials 738-739 (March 2015): 1231–35. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.1231.

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At present P2P is widely applied on the Internet. But it still has a safety hazard because of the special feature of dynamic and anonymity of P2P.This paper designs a model of P2P trust based on fuzzy degree of nodes' credit. It computes the fuzzy degree of nodes' credit according to the historic records and the theory of fuzzy mathematics, and the result is used as the basis of choice of P2P transaction. The fuzzy degree of nodes' credit will be increased and decreased according to the behavior of the node, establishing the dynamic and reasonable mechanism of rewards and punishment. Experimental results show that the model designed in this paper has a better performance in the parts of trade success rate and network load.

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Plecka, Przemysław, and Krzysztof Bzdyra. "The Software Cost Estimation Method Based on Fuzzy Ontology." Foundations of Management 6, no. 2 (December 1, 2014): 21–30. http://dx.doi.org/10.1515/fman-2015-0008.

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Abstract In the course of sales process of Enterprise Resource Planning (ERP) Systems, it turns out that the standard system must be extended or changed (modified) according to specific customer’s requirements. Therefore, suppliers face the problem of determining the cost of additional works. Most methods of cost estimation bring satisfactory results only at the stage of pre-implementation analysis. However, suppliers need to know the estimated cost as early as at the stage of trade talks. During contract negotiations, they expect not only the information about the costs of works, but also about the risk of exceeding these costs or about the margin of safety. One method that gives more accurate results at the stage of trade talks is the method based on the ontology of implementation costs. This paper proposes modification of the method involving the use of fuzzy attributes, classes, instances and relations in the ontology. The result provides not only the information about the value of work, but also about the minimum and maximum expected cost, and the most likely range of costs. This solution allows suppliers to effectively negotiate the contract and increase the chances of successful completion of the project.

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Jaggi, Chandra K., V. S. S. Yadavalli, Anuj Sharma, and Sunil Tiwari. "A Fuzzy EOQ Model with Allowable Shortage under Different Trade Credit Terms." Applied Mathematics & Information Sciences 10, no. 2 (March 1, 2016): 785–805. http://dx.doi.org/10.18576/amis/100239.

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Kheir, Naim A., Mutasim A. Salman, and Niels J. Schouten. "Emissions and fuel economy trade-off for hybrid vehicles using fuzzy logic." Mathematics and Computers in Simulation 66, no. 2-3 (June 2004): 155–72. http://dx.doi.org/10.1016/j.matcom.2003.11.007.

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Leu, Sou-Sen, An-Ting Chen, and Chung-Huei Yang. "A GA-based fuzzy optimal model for construction time–cost trade-off." International Journal of Project Management 19, no. 1 (January 2001): 47–58. http://dx.doi.org/10.1016/s0263-7863(99)00035-6.

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Stroomer, Chad, and David E. A. Giles. "Real Output Convergence and Trade Openness: Fuzzy Clustering and Time Series Evidence." International Trade Journal 22, no. 2 (May 5, 2008): 115–55. http://dx.doi.org/10.1080/08853900801970502.

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