Fuzzy Optimization
Mehrdad Rasoulzadeh; Seyyed Ahmad Edalatpanah; mohammad fallah; esmaeil najafi
Abstract
Goal: Increasing the wealth of shareholders is one of the most important goals of financial management. This issue is always intertwined with the two concepts of risk and return at the same time, so that hareholders always seek to increase portfolio return by controlling and minimizing risk, or seeking ...
Read More
Goal: Increasing the wealth of shareholders is one of the most important goals of financial management. This issue is always intertwined with the two concepts of risk and return at the same time, so that hareholders always seek to increase portfolio return by controlling and minimizing risk, or seeking to reduce risk at a certain level of Returns are expected. For this purpose, investors mainly use the concepts of fundamental analysis and paying attention to the internal structure and financial performance of companies, or paying attention to the changes and price fluctuations of stocks in the market, or a combination of both methods.Research methodology: In this research, by combining the Markowitz model with fuzzy returns with the network data coverage analysis model, we will achieve a multi-objective model, which by considering the performance of companies based on some financial ratios and its effect on the stock market value, Also, price fluctuations will try to introduce stock portfolios in the best possible situations in terms of risk, return and efficiency of the stock portfolio. Finally, in order to use the model in selecting an optimal portfolio, 50 companies were selected from the active companies in the Tehran Stock Exchange, and the said model was implemented on them. Also, multi-objective algorithm with non-dominated sorting was used to solve the model.Findings: The results obtained from the implementation of the model on 50 companies active in the stock exchange show that the use of the proposed model is better than the use of any of Markobetz's models or network data coverage analysis alone, and also the ratio The non-network model provides investors with better results in terms of returns, risk and efficiency.
Fuzzy Optimization
Malihe Niksirat; Majid Abdolrazzagh nezhad
Abstract
Purpose: In this paper, a Binary Fuzzy Linear Programming Problem (BFLPP) with fuzzy objective function and fuzzy constraints is considered. The purpose of this paper is to propose a new approach that solves the problem based on kerre’s adapted method that maintains the assumption of being fuzzy ...
Read More
Purpose: In this paper, a Binary Fuzzy Linear Programming Problem (BFLPP) with fuzzy objective function and fuzzy constraints is considered. The purpose of this paper is to propose a new approach that solves the problem based on kerre’s adapted method that maintains the assumption of being fuzzy in the solving process. Therefore, the solution is more consistent with the conditions of uncertainty governing the problem.
Methodology: In this paper, a new fuzzy branch-and-bound approach based on Kerre's adapted method is proposed to solve the fuzzy binary integer programming problem. In each node of the branch-and-bound tree, the linear relaxation of the fuzzy problem is solved with a new fuzzy simplex method based on Kerre’s adapted method.
Findings: Numerical examples are presented to illustrate the proposed method step by step and the results are compared with other approaches that solve fuzzy binary integer programming problems.
Originality/Value: Unlike the available defuzzification procedures and fuzzy ranking functions in the literature of the research problem, the proposed approach considers the assumption of being fuzzy in the solution process and thus offers a more realistic solution.
Fuzzy Optimization
Mahin Ashouri; Abdollah Hadi-Vencheh; Ali Jamshidi
Abstract
Purpose: This study aims to tackle the challenging facility location selection problem in Multiple Criteria Decision Making (MCDM) scenarios, explicitly focusing on type-1 fuzzy MCDM issues. The research introduces Interval Valued Fuzzy Numbers (IVFNs) to express ratings, addressing the difficulty in ...
Read More
Purpose: This study aims to tackle the challenging facility location selection problem in Multiple Criteria Decision Making (MCDM) scenarios, explicitly focusing on type-1 fuzzy MCDM issues. The research introduces Interval Valued Fuzzy Numbers (IVFNs) to express ratings, addressing the difficulty in determining precise membership degrees for fuzzy sets.Methodology: The proposed IVF-COPRAS method, centered on uncertainty risk reduction, is employed to enhance decision-making reliability in IVF decision problems. This methodology is applied to a real-world case involving the selection of a location for municipal wet waste landfill pits in a major Iranian city. Comparative analyses with other methods are conducted to assess the proposed approach.Findings: The study demonstrates the effectiveness of the IVF-COPRAS method in addressing facility location selection problems within MCDM. By utilizing IVFNs, the method successfully manages uncertainty, leading to more reliable decisions. Application to a practical scenario highlights the method's efficacy, and the comparative analysis provides insights into its performance relative to other methods.Originality/Value: This research contributes a novel approach with the IVF-COPRAS method for handling facility location selection challenges in MCDM. The reliance on IVFNs offers a unique perspective on uncertainty in decision-making, enhancing decision reliability. The real-world application emphasizes the method's practical significance, providing a valuable contribution to MCDM research and offering a methodological tool for similar decision-making problems across diverse domains.
Fuzzy Optimization
Malihe Niksirat
Abstract
Purpose: During the Corona virus epidemic and in order to comply with the rules of social distancing, public transport operators have to operate with less capacity. Because demand may be overcapacity in different areas at different times of the day, drivers are forced to refrain from serving passengers ...
Read More
Purpose: During the Corona virus epidemic and in order to comply with the rules of social distancing, public transport operators have to operate with less capacity. Because demand may be overcapacity in different areas at different times of the day, drivers are forced to refrain from serving passengers at certain stations to avoid overcrowding.Methodology: The purpose of this paper is to develop decision support tools to prevent congestion of vehicles. Also, in order to consider the real conditions, two types of fuzzy and scenario-based uncertainty are considered. A dynamic nonlinear integer programming model is introduced to obtain the optimal service pattern for vehicles that are ready to be dispatched. To overcome the combined uncertainty of the problem, possibility theory has been proposed as a new fuzzy stochastic programming approach that has significant advantages.Findings: The model is clearly strikes a balance between observing social distancing by reducing the capacity of vehicles and reducing the waiting time of passengers who lose services. Numerical examples are provided to illustrate the proposed concepts and model and to compare the results.Originality/Value: The proposed decision support model can suggest service patterns for different lines service and can assess public transport operators to evaluate the advantages and disadvantages of implementing epidemic-based service patterns due to operational advances and demand level of travelers.
Fuzzy Optimization
Gohar Shakouri; Seyed Hadi Nassery; Mohammad Mahdi Paydar
Abstract
Purpose: The transportation problem, as one of the most important and most practical models related to linear programming, has always been of interest to researchers. Due to the lack of accurate information, variable economic conditions, uncontrollable factors and especially variable conditions of available ...
Read More
Purpose: The transportation problem, as one of the most important and most practical models related to linear programming, has always been of interest to researchers. Due to the lack of accurate information, variable economic conditions, uncontrollable factors and especially variable conditions of available resources, to adapt to the real conditions, we are faced with a kind of uncertainty, both flexibility in constraints and fuzzy nature of the parameters. Hence, one method to express the conditions of this modeling is to use flexible fuzzy numbers that make it more adaptable to real conditions.Methodology: In this research, after reviewing the research literature, the transportation problem is modeled by considering the flexible-interval fuzzy supply constraint. Then, for the solution process, a flexible fuzzy approach to the proposed model is studied.Findings: Numerical example analysis indicates that parametric linear programming approach offers a reliable design so that the decision maker can obtain a better selection of resources with the most satisfaction.Originality/Value: In this research, parametric approach with flexible relationship is discussed and based on the research results, the solution is obtained with the most satisfaction in constraints.
Fuzzy Optimization
Madineh Farnam; Majid Darehmiraki
Abstract
Purpose: In working with Interval-valued intuitionistic fuzzy sets according to considering the membership and non-membership function simultaneously, as well as the interval of the data type, we face to a lot of flexibility to allocate data by the decision maker. Comparison ...
Read More
Purpose: In working with Interval-valued intuitionistic fuzzy sets according to considering the membership and non-membership function simultaneously, as well as the interval of the data type, we face to a lot of flexibility to allocate data by the decision maker. Comparison between them, as one of the first concepts in the decision-making process, does not seem so simple. For this purpose, in this paper we present an integrated and efficient method and a new way to prioritize interval-valued intuitionistic fuzzy numbers. Then we apply this method to assess the qualitative qualification of contractors.Methodology: Use interval valued intuitionistic fuzzy sets along with multi criteria decision making.Findings: New ranking method of interval valued intuitionistic fuzzy sets is apllied in evaluating operational units. In addition, by giving a practical example while describing the process performance, the output of the work is observed.Originality/Value: A new method is proposed to determine the preference between interval valued intuitionistic fuzzy sets. In addition, an efficiency process is introduced to assess the qualitative qualification of contractors.
Fuzzy Optimization
Bahavar Azarmizad; Kamaleddin Rahmani; Alireza Bafandeh Zendeh; Sirous Fakhimiazer
Abstract
Purpose: Statistical Process Control (SPC) is a powerful set of problem-solving tools that stabilize production processes and increase the ability to produce high quality product. Classic control diagrams, using precise and definite data, place production processes into two groups: under control or out ...
Read More
Purpose: Statistical Process Control (SPC) is a powerful set of problem-solving tools that stabilize production processes and increase the ability to produce high quality product. Classic control diagrams, using precise and definite data, place production processes into two groups: under control or out of control; while Fuzzy sets by defining continuous membership functions and using ambiguous, indefinite data, triangular and trapezoidal Fuzzy numbers, classify into these categories: under control, relatively under control, relatively out of control and out of control which express the quality level of the product more realistically.Methodology: This research is an applied and descriptive research with the aim of designing an applied model of Statistical Process Control by Fuzzy Mode and Middle Fuzzy and comparing its results with Classical Method in Dadash Baradar Ind. Co. in Tabriz. This method of data collection to run the model follows the sampling system at the inspection station and is in the form of 30 samples of 50 chocolates.Findings: According to the seven defects of chocolate, which include: color, taste, acidity, sugar blossom, tissue factors and foreign substances, the nature of the produced chocolate was determined. In the Classical Method, 28 cases under control and only 2 cases out of control were identified, but in the study with Fuzzy SPC Method, 20 samples under control, 4 samples relatively under control, 4 samples relatively out of control and 2 samples were out of control.Originality/Value: Research results shows the sensitivity of the Fuzzy SPC Method compared to the Classical Method; as a result, identifying process changes is more accurate and faster, and accordingly practical suggestions have been provided to the company.
Fuzzy Optimization
Morteza Goli; Hadi Nasseri; Mehrdad Ghaznavi
Abstract
In this paper, we deal with a linear programming problem with non-symmetric trapezoidal intuitionistic fuzzy numbers. In recent years, many authors have studied the symmetric trapezoidal intuitionistic fuzzy numbers. After defining a ranking function and arithmetic operations on these numbers, they solved ...
Read More
In this paper, we deal with a linear programming problem with non-symmetric trapezoidal intuitionistic fuzzy numbers. In recent years, many authors have studied the symmetric trapezoidal intuitionistic fuzzy numbers. After defining a ranking function and arithmetic operations on these numbers, they solved the intuitionistic fuzzy linear programming problem.But the main problem with their method was that only available for symmetric trapezoidal intuitionistic fuzzy numbers. Now in order to overcome this limitation, in this paper, we present a new arithmetic and a new ordering for non-symmetric trapezoidal intuitionistic fuzzy numbers. Then, we present the general model of an intuitionistic fuzzy linear programming problems and prove a number of important theorems for solving it. Then we present the intuitionistic fuzzy simplex algorithm and finally, by presenting two examples, we will show the application of this new approach and show its superiority over the fuzzy mode.
Fuzzy Optimization
Morteza Shafiee; Hilda Saleh; Atefeh Kaveh
Abstract
Assessing the reliability and availability of the production system reduces the likelihood of sudden and costly stops, which is very risky. To this end, this paper attempts to provide a new way to determine the reliability and availability of a production system, which can be used for a variety of failure ...
Read More
Assessing the reliability and availability of the production system reduces the likelihood of sudden and costly stops, which is very risky. To this end, this paper attempts to provide a new way to determine the reliability and availability of a production system, which can be used for a variety of failure components such as materials, supplies, personnel and machinery. Therefore, using Fuzzy Bayesian Approach, unrealistic events that are actually created in a production system have been processed and the proposed model has been used to assess the condition of Pegah Fars milk factory, so that the rate of failure and repair and reliability of components and system with Bayesian method was calculated. And because the available information space is uncertain, the reliability parameters became fuzzy. Then the availability of the components and then the whole system was calculated using the formula provided by Martz and Waller and the Bayesian method, and the parameters of availability were converted into fuzzy. Finally, the information obtained about the reliability and availability of the system and components were analyzed, that the results show the improved approach, provides a more accurate estimate of reliability and availability.
Fuzzy Optimization
Nemat Allah Taghi-Nezhad; Fatemeh babakordi
Abstract
Quadratic programming problem is one of the important problem of classic optimization problems that the aim is to find the maximum or minimum amount of a quadratic function under linear constraints. In this paper, the quadratic programming problem where its parameters are all nonnegative fuzzy numbers ...
Read More
Quadratic programming problem is one of the important problem of classic optimization problems that the aim is to find the maximum or minimum amount of a quadratic function under linear constraints. In this paper, the quadratic programming problem where its parameters are all nonnegative fuzzy numbers is discussed and a new algorithm based on fuzzy operations and fuzzy arithmetic is presented where reduced the fuzzy model into three smaller and more simple crisp problem. Then, by solving these crisp models using conventional algorithms such as SQP and by combining these solutions, the optimal solution of the fuzzy problem is obtained. Finally, an example is solved to implement the proposed algorithm and show the applicability of it.
Fuzzy Optimization
Shokouh Sargolzaei; Faranak Hosseinzadeh Saljooghi; Hadi Aghayari
Abstract
Since much of human reasoning is based on imprecise, vague and subjective values, most of the decision-making processing, in reality, requires handling and evaluation of fuzzy numbers. Ranking fuzzy numbers are one of the very important research topics in fuzzy set theory because it is a base of decision-making ...
Read More
Since much of human reasoning is based on imprecise, vague and subjective values, most of the decision-making processing, in reality, requires handling and evaluation of fuzzy numbers. Ranking fuzzy numbers are one of the very important research topics in fuzzy set theory because it is a base of decision-making in applications. Although so far, many methods for ranking of fuzzy numbers have been discussed broadly, most of them contained some shortcomings, such as the requirement of complicated calculations, inconstancy with human intuition and indiscrimination. In this paper, we introduce a new method by using the affine combination on the circumcenter. This method ranks various types of fuzzy numbers which include normal, generalized trapezoidal, and triangular fuzzy numbers along with crisp numbers with the particularity that crisp numbers are to be considered particular cases of fuzzy numbers. The advantages of the new proposed are that it can be applied for most of the defuzzification and the calculation is far simple and easy than previous methods. The effectiveness of the proposed method and its advantages is demonstrated by numerical examples, comprehensive comparing the different ranking method with this method and also its benefits will be illustrated by the numerical example, as well as a case study on supply chain management.
Fuzzy Optimization
Mona Khodagholi; Ardeshir dolati; ali hoseinzadeh
Abstract
Facility location problems are among the important operation research and management problems. Locating storehouses, hospitals, rescue-relief stations, military bases,bank branches, etc are some of its famous applications. The aim of solving such problems is to determine the best location for the facilities ...
Read More
Facility location problems are among the important operation research and management problems. Locating storehouses, hospitals, rescue-relief stations, military bases,bank branches, etc are some of its famous applications. The aim of solving such problems is to determine the best location for the facilities to ensure their maximum efficiency to provide services for customers. Location problems have recently been studied in the light of inverse approach, various classic algorithms for being introduced for their solution. 1-median problem is one of the most famous functions of target location. However, given that real world parameters are not exact, we decided to investigate fuzzy 1-median inverse problem. Based on alfa-cut concept for fuzzy triangular numbers, first we obtain a fully fuzzy linear programming model which proposes a range for different levels of certainty. Then we propose a solution method based on range account. Thus the solution of 1-median inverse problem with fuzzy parameters corresponds to its classic solution. To help better understand the proposed method, we show a numerical example.