Fuzzy optimization
Mohammad Hossein Kabgani
Abstract
Selecting appropriate locations for Municipal Solid Waste (MSW) management facilities, such as landfills, is an important issue in rapidly developing regions. Multiple alternatives and evaluation attributes need to be analyzed to finalize the locations of these facilities. The selection of a landfill ...
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Selecting appropriate locations for Municipal Solid Waste (MSW) management facilities, such as landfills, is an important issue in rapidly developing regions. Multiple alternatives and evaluation attributes need to be analyzed to finalize the locations of these facilities. The selection of a landfill site in an urban area is a critical issue due to the involvement of many parameters. The decisive parameters are environmental, economic, and social, some of them conflicting, making landfill site selection a tedious and complex process. Multi Attribute Decision Making (MADM) approaches are found to be very effective for ranking several potential locations and, hence, selecting the best among them based on the identified attributes. Therefore, this study presents a two-stage MADM model that also accounts for all possible combinations of locations. This study evaluates economic, environmental, social, and technical attributes based on realistic conditions. Based on the results, 15 attributes are first identified through a comprehensive literature review and with the help of municipal officials during field surveys. These attributes are categorized into four types, i.e., economic, technical, environmental, and social, based on their respective propensity.In the second step, a statistical analysis questionnaire was distributed among the study population, and Cronbach's alpha was explained for all four main factors of the study. Therefore, in the last step, the rank of all research variables was calculated using the Nonlinear analysis method. Based on the results of this study, the technical variable was ranked first, the economic variable was ranked second, and the environmental and social variable was ranked third. This article has three theoretical, practical, and technical contributions. Also, this article provides a clear explanation of the theoretical contribution related to the accumulated knowledge, both in the introduction and theoretical background sections of the article. Therefore, studying the past research describes a relatively complete background of the planned theoretical contributions of this article compared to the previous research. Therefore, the theoretical contribution of this article solves the scientific gap about effective indicators for determining the location of waste disposal. From the point of view of practical contribution, this article presents practical concepts related to managers and experts and has practical suggestions presented in the conclusion section. Also, the technical contribution of this article is presented by combining fuzzy logic and Nonlinear mathematical programming.
Fuzzy optimization
Hamiden Abdelwahed Khalifa
Abstract
In this paper, a multi-objective assignment problem with fuzzy parameters (FMOASP) is introduced. These fuzzy parameters are characterized by an interval-valued fuzzy numbers instead of fuzzy numbers. The signed distance ranking of interval- valued fuzzy numbers of the parameters are not ...
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In this paper, a multi-objective assignment problem with fuzzy parameters (FMOASP) is introduced. These fuzzy parameters are characterized by an interval-valued fuzzy numbers instead of fuzzy numbers. The signed distance ranking of interval- valued fuzzy numbers of the parameters are not random but bear well-defined relationship to one another. A new approach namely, optimal flowing method is proposed to obtain the ideal and the set of all fuzzy efficient solutions for the problem. A numerical example is given to demonstrate the computational efficiency of the proposed approach.
Fuzzy optimization
Ladji Kane; Hawa Bado; Moctar Diakite; Moussa Konate; Souleymane Kane; Koura Traore
Abstract
The aim of this paper is to introduce a new technique for improve the methods for solving the Semi-fully Fuzzy Linear Programming Problems. An algorithm is proposed to find the fuzzy optimal solution of Semi-fully Fuzzy Linear Programming Problems. This technique is also best fuzzy optimal solution in ...
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The aim of this paper is to introduce a new technique for improve the methods for solving the Semi-fully Fuzzy Linear Programming Problems. An algorithm is proposed to find the fuzzy optimal solution of Semi-fully Fuzzy Linear Programming Problems. This technique is also best fuzzy optimal solution in the literature and illustrated with numerical examples.
Fuzzy optimization
S. H. Mirzaei; A. Salehi
Abstract
In many real applications, the data of production processes cannot be precisely measured. Hence the input and output of Decision Making Units (DMUs) in Data Envelopment Analysis (DEA) may be imprecise or fuzzy-numbered. In original DEA models, inputs and outputs are measured by exact values on a ratio ...
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In many real applications, the data of production processes cannot be precisely measured. Hence the input and output of Decision Making Units (DMUs) in Data Envelopment Analysis (DEA) may be imprecise or fuzzy-numbered. In original DEA models, inputs and outputs are measured by exact values on a ratio scale, therefore conventional DEA can't easily measure the performance of DMUs and rank them. The researchers have introduced mane deferent model for ranking DMUs by fuzzy number. In this paper, we proposed a new method by using the Tchebycheff norm for ranking DMUs with fuzzy data. We explain our method by numerical example with the triangular fuzzy number.
Fuzzy optimization
S. K. Das
Abstract
The Fuzzy Linear Programming problem has been used as an important planning tool for the different disciplines such as engineering, business, finance, economics, etc. In this paper, we proposed a modified algorithm to find the fuzzy optimal solution of fully fuzzy linear programming problems with equality ...
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The Fuzzy Linear Programming problem has been used as an important planning tool for the different disciplines such as engineering, business, finance, economics, etc. In this paper, we proposed a modified algorithm to find the fuzzy optimal solution of fully fuzzy linear programming problems with equality constraints. Recently, Ezzati et al. (Applied Mathematical Modelling, 39 (2015) 3183-3193) suggested a new algorithm to solve fully fuzzy linear programming problems. In this paper, we modified this algorithm and compare it with other existing methods. Furthermore, for illustration, some numerical examples and one real problem are used to demonstrate the correctness and usefulness of the proposed method.
Fuzzy optimization
H. Nasseri; M. Morteznia; M. Mirmohseni
Abstract
Supplier selection is one of the most critical activities of purchasing management in a supply chain. Because selecting right suppliers helps reduce purchasing costs, improve quality of final products and services, etc. In a real situation, for a supplier selection problem, most of the input information ...
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Supplier selection is one of the most critical activities of purchasing management in a supply chain. Because selecting right suppliers helps reduce purchasing costs, improve quality of final products and services, etc. In a real situation, for a supplier selection problem, most of the input information is not known precisely, since decision making deal with human judgment and comprehension and its nature includes ambiguity. In fact, on the one hand, deterministic models cannot easily take this vagueness into account. In these cases, the theory of fuzzy sets is one of the best tools to handle uncertainty. On the other hand, Kumar et al. proposed a new approach to find the fuzzy optimal solution of fully fuzzy linear programming problem. So, using this approach in this paper, we present a new mixed integer multi objective linear programming model for supplier selection problem. Due to uncertainty of the data, in continuation, we present a new method to solve multi objective fully fuzzy mixed integer linear programming and implement the method to supplier selection problem. Computational results present the application of the method and the proposal solving method.
Fuzzy optimization
M. M. Tavakoli; B. Molavi; H. Shirouyehzad
Abstract
In recent years, researchers in their studies considered human capital as one of the most important capitals of every organization and even some of them placed it beyond this definition and introduced it as the unique factor of creating the competitive advantage in the organization. Due to the importance ...
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In recent years, researchers in their studies considered human capital as one of the most important capitals of every organization and even some of them placed it beyond this definition and introduced it as the unique factor of creating the competitive advantage in the organization. Due to the importance of human capital management, by evaluating the performance of human capital management system, managers can be aware of their organization’s status from the perspective of human capital management creation and perform corrective practices better. In this study, a method for the performance evaluation and ranking of organizational unit is presented using fuzzy DEA. Therefore in the beginning, the performance of organizational units was evaluated using fuzzy DEA and then with the use of sensitivity analysis, the most effective criteria on the efficiency of organizational units were determined. Then using the efficiency of organizational units in the best and the worst states, ranking of organizational units has been paid. Finally to examine the functionality of the proposed method, Foolad Technic Company has been chosen as a case study and the procedure has been implemented in this company.
Decision analysis and methods
H. R. Seiti; A. Behnampour; D. M. Imani; M. Houshmand
Abstract
Failure Modes and Effects Analysis (FMEA) is being widely used to detect and eliminate known and/or potential failures, problems, errors and so on from system design, process, and/or service, before they reach the customer. It can be done by calculating the risk priority number which is the product of ...
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Failure Modes and Effects Analysis (FMEA) is being widely used to detect and eliminate known and/or potential failures, problems, errors and so on from system design, process, and/or service, before they reach the customer. It can be done by calculating the risk priority number which is the product of three factors: occurrence, severity and detectability. A lot of efforts have been made to overcome the shortcomings of the crisp RPN calculation and extend it to fuzzy environment. In this study, the presented fuzzy approach allows experts to describe the variables of risk priority number using linguistic terms by applying the method of fuzzy axiomatic design (FAD). At the final part of this paper a hypothetical case study demonstrated the applicability of the FMEA model under fuzzy environment.