Search

‎Machines can model and improve the human mind’s capabilities through artificial intelligence‎. ‎One of the most popular tools of artificial intelligence is fuzzy sets‎, ‎which can capture and model the vagueness and impreciseness in human thoughts‎. ‎This paper‎, ‎first of all‎, ‎introduces the recent extensions of ordinary fuzzy sets and then presents a literature review on the integration of fuzzy sets with other artificial intelligence techniques such as automated reasoning‎, ‎autonomous agents‎, ‎multi-agent systems‎, ‎machine learning‎, ‎case-based reasoning‎, ‎deep learning‎, ‎information reasoning‎, ‎information representation‎, ‎natural language processing‎, ‎symbolic reasoning‎, ‎and neural networks‎. ‎Graphical illustrations of literature review results are presented for each of these integrated artificial intelligence techniques‎. ‎The results of a patent search on fuzzy artificial intelligence are also given‎.

Intuitionistic Fuzzy Sets with Ordered Pairs (IFSOP) are the recent extension of intuitionistic fuzzy sets by incorporating functional and dysfunctional points of view into the definition of membership functions. This paper extends the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) method to the Intuitionistic Fuzzy TOPSIS (IF TOPSIS) with ordered pairs method and applies it to a multi-criteria risk-based supplier selection problem under fuzziness. IF TOPSIS with ordered pairs involves finding a positive ideal solution and a negative ideal solution, and measuring the distance between each alternative and these solutions. The final ranking of the alternatives is obtained based on the proportion of distances between the positive and negative ideal solutions. By asking functional and dysfunctional questions in this ranking process, the developed IF TOPSIS with ordered pairs method incorporates the accuracy and consistency of expert judgments, enhancing the decision-making process. A sensitivity analysis is also presented in order to show the robustness of the rankings obtained by IF TOPSIS with ordered pairs.

The utilization of renewable energy sources has come into prominence especially over the last two decades. In the literature, various methods have been utilized for the evaluation of renewable energy sources. In particular, multi-attribute decision making (MADM) methods have been widely used throughout the renewable energy literature for several purposes such as evaluation of energy policies, selection of the most suitable renewable energy source for electricity generation, evaluation of renewable energy sources, identification of the optimal site for a renewable energy facility, and selection of the best one among energy alternatives. In the scope of this paper, the studies employing MADM methods in renewable energy applications have been taken into consideration. The main aim of the study is to determine the reasons and factors explaining why these methods have been employed. It can be concluded that Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), ELimination Et Choix Traduisant la REalité (ELECTRE) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) have come into the forefront as the most widely employed methods in the literature. However, there are a few studies employing outranking methods, ELECTRE and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) for the purpose of evaluating renewable energy investments/projects. Furthermore, in the literature, there are limited papers considering utilization of renewable energy sources such as geothermal, hydro, and waste. Finally, this study indicates that renewable energy exploitation is a quite suitable topic to use MADM methods. Keywords: Renewable energy, Sustainability, Multi-attribute decision making, Analytic hierarchy process, Analytic network process

Organizations, in their pursuit of accomplishing their vision and goals, need effective management of human resources. Performance Management, among other Human Resources Management (HRM) practices, is the central function, as it delivers the necessary data that complements and enables the other functions. Building an effective performance management system is a multicriteria problem that requires contribution from experts having diverse backgrounds. Moreover, performance management is an inherently vague concept since almost the whole process requires linguistic assessments rather than numerical ones. Hence, to handle all those issues, an intuitionistic fuzzy multi-criteria and multi-expert analytical hierarchy process (AHP) based management model is proposed in this paper. In the determination of the criteria weights of the model, both the aggregated and compromised assessments of the experts are used in order to observe the effects of these two methods on the results. A numerical application is given to illustrate the use of the model.

Nowadays, unpaid invoices and unpaid credits are becoming more and more common. Large amounts of data regarding these debts are collected and stored by debt collection agencies. Early debt collection processes aim at collecting payments from creditors or debtors before the legal procedure starts. In order to be successful and be able to collect maximum debts, collection agencies need to use their human resources efficiently and communicate with the customers via the most convenient channel that leads to minimum costs. However, achieving these goals need processing, analyzing and evaluating customer data and inferring the right actions instantaneously. In this study, fuzzy inference based intelligent systems are used to empower early debt collection processes using the principles of data science. In the paper, an early debt collection system composed of three different Fuzzy Inference Systems (FIS), one for credit debts, one for credit card debts, and one for invoices, is developed. These systems use different inputs such as amount of loan, wealth of debtor, part history of debtor, amount of other debts, active customer since, credit limit, and criticality to determine the output possibility of repaying the debt. This output is later used to determine the most convenient communication channel and communication activity profile.

Due to the differences between regions and sub-regions in the countries, some problems come out especially in economic and social life. The issue of differences of regions has been widely implemented to evaluate the economic performance of Turkey in many disciplines. The objective of this paper is to evaluate the efficiency of 26 sub-regions of NUTS-2 classification using integration Fuzzy Analytic Hierarchy Process (FAHP) with Data Envelopment Analysis (DEA). The integrated FAHP/DEA method comprises two stages. In the first stage, linguistic terms are used to determine the decision makers’ opinion and are converted to quantitative forms by using FAHP methods. Subsequently, in the second stage, DEA method is applied to obtain relative efficiency of sub-regions in Turkey. The integrated FAHP/DEA method is illustrated with a real case study.

Since people well know the threats of inorganic agriculture to their health, they are more interested in organic agriculture than ever. Organic agriculture is expected to play a major role for a healthy world in the future whereas inorganic agriculture nowadays increases the volume of agricultural production and presents lower priced foods but causes health problems. The agricultural investments are generally evaluated by using linguistic terms since most of the evaluation criteria are intangible and inherently require imprecise data to be used. In this paper, we analyze six types of agricultural investment alternatives using eight different criteria based on linguistic data. One of the most-used multi-criteria decision-making methods, TOPSIS is used under fuzziness for the solution of this problem. A sensitivity analysis is also given to examine the robustness of the decision.

Evaluation based on Distance from Average Solution (EDAS) is a new multicriteria decision making (MCDM) method, which is based on the distances of alternatives from the average scores of attributes. Classical EDAS has been already extended by using ordinary fuzzy sets in case of vague and incomplete data. In this paper, we propose an interval-valued intuitionistic fuzzy EDAS method, which is based on the data belonging to membership, nonmembership, and hesitance degrees. A sensitivity analysis is also given to show how robust decisions are obtained through the proposed intuitionistic fuzzy EDAS. The proposed intuitionistic fuzzy EDAS method is applied to the evaluation of solid waste disposal site selection alternatives. The comparative and sensitivity analyses are also included.

In some cases, the specification limits of a quality characteristic should be defined under uncertain information. In the literature, process capability analyses have been handled by using type-1 fuzzy sets under fuzziness up to now. In this paper, we develop the concept of type-2 fuzzy quality and use it in the calculation of process capability. Lower and upper specification limits are considered as type-2 fuzzy sets. We define the addition and subtraction operations for introducing interval type-2 fuzzy process capability indices. We can calculate the nonconforming percentage of the production using the developed equations. We present some numerical examples to show the applicability of the proposed equations.

Almost all the worldwide and nationwide companies utilize advertising to increase their sales volume and profit. These companies pay millions of dollars to reach consumers and announce their products or services. This forces companies to evaluate advertising effects and check whether ads meet companys strategies. They need to evaluate the ads not only after announcement, but also before advertising, i.e. they can be one step ahead by predicting the future advertising awareness through artificial intelligence tools such as fuzzy systems and neural networks. In this study, we propose to use adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) to analyze advertising decision making. ANFIS creates fuzzy rules and trains the neural network using given input data. This training ability of ANFIS and ANN leads to predicting the advertising awareness outputs. Here, we investigate three advertising awareness outputs, namely, top of mind, share of voice, and spontaneous awareness. In order to achieve the valid predictions, data are randomly divided into training data with 70 percent, validation data with 15 percent, and testing data with remained 15 percent of data. The correlation between actual data and predictions are calculated to check the accuracy of the predicted outputs.

Modern manufacturing firms should be supported by effective maintenance to become successful in their operations. One of the approaches for improving the performance of maintenance activities is to implement a total productive maintenance (TPM) strategy. Overall equipment effectiveness (OEE) is the key measure of TPM. According to the results of the literature review, the performance elements measured by the OEE tool are not sufficient to describe the effectiveness of TPM implementation. Hence, we aim at developing and evaluating new performance measures oriented towards the quantification of TPM implementation effectiveness under fuzzy environment. For the evaluation of each performance measure, at first, the nominal group technique has been used. Then to determine whether these performance measures are statistically significant, conjoint analysis based experimental design has been applied. In the second step, COmplex PRo-portional ASsessment of alternatives with Grey relations (COPRAS-G) and the fuzzy COPRAS method has been developed to evaluate these performance measures in TPM. Proposed fuzzy COPRAS method gives the reassuring results of ranking newly developed performance measures in TPM.

Fuzzy sets have a great progress in every scientific research area. It found many application areas in both theoretical and practical studies from engineering area to arts and humanities, from computer science to health sciences, and from life sciences to physical sciences. In this paper, a comprehensive literature review on the fuzzy set theory is realized. In the recent years, ordinary fuzzy sets have been extended to new types and these extensions have been used in many areas such as energy, medicine, material, economics and pharmacology sciences. This literature review also analyzes the chronological development of these extensions. In the last section of the paper, we present our interpretations on the future of fuzzy sets.

Innovation is the way of transforming the resources of a company through the creativity of people into new resources and wealth. Innovation investments are essential instruments in a company’s competitive productivity and profitability strategy. Evaluation of innovation investments is a multicriteria decision making problem with many conflicting tangible and intangible criteria. Vague nature of this evaluation requires a fuzzy multicriteria methodology. In this paper we propose a fuzzy multicriteria method to evaluate technological innovation investments using eight different criteria. Fuzzy TOPSIS method is used in this evaluation and a sensitivity analysis is given. First published online: 07 Sep 2015

Effectiveness of maintenance management is directly related to critical parameters of technical systems such as efficiency, reliability, and economic life. In practice, this process is executed via procedures on selected adequate maintenance method among which the alternatives such as Total Productive Maintenance, Planned Maintenance, Preventive Maintenance, Predictive Maintenance, Reactive Maintenance, or Reliability Centered Maintenance. However, increasing system complexity due to the contributions of technological developments requires implementing more advance maintenance planning techniques. In this study, an integrated maintenance management system is presented based on Fuzzy Information Axioms methodology for shipboard systems under various characteristics and functional attributes. An extended and more effective maintenance management systematic is developed for merchant ships using applied decision model outcomes.

People buy insurance to protect themselves against possible financial loss in the future. Health insurance provides protection against the possibility of financial loss due to health care use. A selection among health insurance options is a multiattribute decision making problem including many conflicting criteria. This problem can be better solved using the fuzzy set theory since human decision making is generally based on vague and linguistic data. We propose an integrated methodology composed of fuzzy AHP and fuzzy TOPSIS to select the best health insurance option. The considered option types, Health Savings Account (HSA), Flexible Spending Accounts (FSA), and Health Reimbursement Arrangement (HRA) are evaluated using eight different criteria under fuzziness. A sensitivity analysis is also realized. First published online: 18 Jun 2015

Decision making is a common process in human activities. Every person or organization needs to make decisions besides dealing with uncertainty and vagueness associated with human cognition. The theory of fuzzy logic provides a mathematical base to model the uncertainities. Hesitant fuzzy linguistic term set (HFLTS) creates an appropriate method to deal with uncertainty in decision making. Managerial decision making generally implies that decision making process conducts multiple and conflicting criteria. Multi criteria decision analysis (MCDA) is a widely applied decision making method. Outranking methods are one type of MCDA methods which facilitate the decision making process through comparing binary relations in order to rank the alternatives. Elimination et Choix Traduisant la Réalité (ELECTRE), means elimination and choice that translates reality, is an outranking method. In this paper, an extended version of ELECTRE I method using HFLTS is proposed. Finally, a real case problem is provided to illustrate the HFLTS-ELECTRE I method.

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.

A municipality improves the quality of community life through its projects and actions. However, project selection and prioritization by municipalities are highly complex processes. Therefore, multicriteria decision making (MCDM) methodologies are very suitable for determining the best alternative. Recently, some studies have concentrated on the selection of the best project alternatives. In this paper, a two phased fuzzy MCDM methodology is proposed for the selection among municipal projects. In the first phase, fuzzy TOPSIS method is used to select the main project group and then fuzzy AHP is used to select the best sub-municipal project. The application of the suggested methodology has been made at the central district municipality in Konya, Turkey.

Strategic decisions such as mergers, acquisitions and joint ventures have a strong effect on firm performance. In order to be successful in highly competitive environments firms have to make right and on time strategic decisions. However, the nature of making the right strategic decision is complex and unstructured since there are many factors affecting such decisions. Moreover these factors are usually hard and vague to evaluate numerically. This study tries to develop a multicriteria decision-making model which considers both the complexity and vagueness of strategic decisions. The weights of the factors are determined by interval type-2 Fuzzy Analytic Hierarchy Process (AHP) and then the best strategy is selected by Hesitant Fuzzy TOPSIS using the determined weights. An application to a multinational consumer electronics company is presented.

Health research and investments are expensive, and its explicit social, health and economic impacts are hard to define. There are many challenges and assumptions in defining specific returns on investment in health research. In the literature, there is no common approach to evaluate health research impacts. Single criterion methods are generally used with validated indicators to track overall outcomes or outcomes in a specific health research area. These methods have the ability of considering only one criterion at a time, which is usually the cost of the investment. A multicriteria method is proposed for taking care of many conflicting criteria of health research investments. The difficulty of measuring intangible criteria is captured by the fuzzy set theory. Fuzzy analytic hierarchy process (AHP) is used for the selection among four possible health research investment alternatives. A sensitivity analysis is made for the changes in the values of various parameters. First published online: 05 Feb 2014

The methodology, Multicriteria Decision Making (MCDM), refers to finding the best alternative from all of the feasible alternatives in the presence of multiple, usually conflicting, decision criteria. Nowadays, intelligent buildings’ performance that is increasingly evidenced in building design and construction has been analyzed by using MCDM techniques. Intelligent buildings (IBs) are also under assessment according to their IB related characteristics and actual circumstances as a MCDM problem. In this paper, two most known MCDM methodologies, Analytic Hierarchy Process (AHP) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), are used for intelligent building assessment under fuzzy environment for dealing with the evaluations’ uncertainty and imprecision in which the expert's comparisons that are represented as fuzzy numbers. For this aim, three intelligent building alternatives for a business centre in Istanbul are evaluated by using these two fuzzy MCDM methods and the obtained ranking results are compared.

Higher education refers to a level of education that is provided at academies, universities, colleges, seminaries, institutes of technology, and certain other collegiate-level institutions. Government investment policy should be concerned with the marginal rate of return when deciding on whether to increase their expenditure on higher education. Government investment in higher education is a decision making problem, which includes multiple and conflicting criteria. We use fuzzy analytic hierarchy process (AHP) to take these criteria into account and to handle vague and incomplete data. We also use fuzzy TOPSIS to compare the results of AHP. A case study for Turkey is realized. In this case study, our multi-criteria decision model evaluates three possible higher education investment alternatives. A sensitivity analysis based on different scenarios of experts’ preferences is also given.

Energy is a critical foundation for economic growth and social progress. It is estimated that 70% of the world energy consumption could be provided from renewable resources by the year 2050. Renewable energy is the inevitable choice for sustainable economic growth, for the harmonious coexistence of human and environment as well as for the sustainable development. The aim of this paper is to evaluate the renewable energy alternatives as a key way for resolving the Turkey's energy-related challenges because of the fact that Turkey's energy consumption has risen dramatically over the past three decades as a consequence of economic and social development. In order to realize this aim, we comparatively use MACBETH and AHP-based multicriteria methods for the evaluation of renewable energy alternatives under fuzziness. We use 4 main attributes and 15 sub-attributes in the evaluation. The potential renewable energy alternatives in Turkey are determined as Solar, Wind, Hydropower, and Geothermal.

In this paper, a novel approach is proposed to determine the electronic system components of a smart clothing system design developed for blinds. The integration of diverse components which are developed and produced by different technologies and materials is a major challenge in a smart clothing system technology. Therefore, an integrated methodology based on fuzzy analytic hierarchy process (AHP) and fuzzy information axiom is used for the solution of this problem.

We consider the markdown optimization problem faced by the leading apparel retail chain. Because of substitution among products the markdown policy of one product affects the sales of other products. Therefore, markdown policies for product groups having a significant crossprice elasticity among each other should be jointly determined. Since the state space of the problem is very huge, we use Approximate Dynamic Programming. Finally, we provide insights on the behavior of how each product price affects the markdown policy.

Multi-Attribute Utility Theory (MAUT) is an evaluation scheme which is very popular by decision makers for evaluating their judgments. According to MAUT, the overall evaluation U(x) of an object x is defined as a weighted addition of its evaluation with respect to its relevant value dimensions. The recent years have witnessed a huge concentration and interest in intelligent buildings’ performance that is increasingly evidenced in building design and construction. Intelligent buildings (IBs) are also under assessment according to their IB related characteristics and actual circumstances. For this aim, in this paper a fuzzy multiple attribute utility model for intelligent building assessment is proposed and three alternative intelligent buildings for a business center in Istanbul are evaluated.

Aircraft's availability is certainly one of the most important features of modern avionic industry. The aircraft maintenance scheduling is one of the major decisions an airline has to make during its operation. When an aircraft maintenance event occurs, the overhaul tasks management process requires the execution of all tasks to perform and has to guarantee the on-time aircraft delivery and the respect of the daily flight schedule. Though maintenance scheduling comes as an end stage in an airline operation, it has potential for cost savings. Maintenance scheduling is an easily understood but difficult to solve problem. Given a flight schedule with aircraft assigned to it, the aircraft maintenance-scheduling problem is to determine which aircraft should fly which segment and when and where each aircraft should undergo different levels of maintenance check. The objective of this paper is to minimize the aircraft maintenance planning time and to show how to create a plan with critical path analyses under fuzzy environment. We use trapezoidal fuzzy numbers for activity times and Activity-on-Node (AON) representation in fuzzy critical path method (FCPM). An illustrative example is given for Aircraft Gas Turbine Engine Repair/Overhaul problem.

Acceptance sampling is primarily used for the inspection of incoming or outgoing lots. Acceptance sampling refers to the application of specific sampling plans to a designated lot or sequence of lots. The parameters of acceptance sampling plans are sample sizes and acceptance numbers. In some cases, it may not be possible to define acceptance sampling parameters as crisp values. These parameters can be expressed by linguistic variables. The fuzzy set theory can be successfully used to cope with the vagueness in these linguistic expressions for acceptance sampling. In this paper, the main distributions of acceptance sampling plans are handled with fuzzy parameters and their acceptance probability functions are derived. Then the characteristic curves of acceptance sampling are examined under fuzziness. Illustrative examples are given.

A hazardous waste is waste that poses substantial or potential threats to public health or the environment. Hazardous waste management is an area of the waste management field concerned with the proper containment, management, and disposal of wastes which could be considered hazardous. In this paper, we use a multicriteria evaluation method, namely VIKOR, for various hazardous waste treatment alternatives under fuzzy environment. These alternatives are physical treatment processes, chemical treatment processes, thermal treatment processes, and biological treatment processes. Under the main criteria, economic, risks, and technical, we consider 11 sub-criteria. The fuzzy set theory let us use linguistic evaluations for the alternatives.

SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis is a commonly used and an important technique for analyzing internal and external environments in order to provide a systematic approach and support for a decision making. SWOT is criticized mostly for considering only qualitative examination of environmental factors, no priority for various factors and strategies, and no vagueness of the factors under fuzziness. In this paper, fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) integrated with fuzzy AHP (Analytical Hierarchy Process) is used to develop fuzzy multi-criteria SWOT analysis in order to overcome these shortcomings. Nuclear power plant site selection, which is a strategic and important issue for Turkey’s energy policy making, is considered as an application case study that demonstrated the applicability of the developed fuzzy SWOT model.

The fuzzy set theory addresses the development of concepts and techniques for dealing with uncertainty or impression conditions. If the collected data from a process include vagueness due to human subjectively or measurement system, fuzzy control charts are available tools for monitoring and evaluating the process. The main contribution of fuzzy control charts is to provide flexibility to the control limits. When sample mean is too close to the control limits and the used measurement system is not so sensitive, the decision may be faulty. In this paper, the fuzzy standard deviation is firstly introduced to obtain fuzzy X and S control charts and then these fuzzy control charts are employed in food industry to monitor if the processes are under control or not. Additionally, the fuzzy X and S control charts are developed for the case that the population parameters are known.

Given the lack of physical constraints of retail banking; attraction, satisfaction, and retention of customers in e-banking mostly depend on the quality of service delivered by the website. Hence, effective assessment and monitoring of website quality have become prerequisites for profitable e-banking. Determining the overall quality of a banking website is a multidimensional issue that involves evaluation of information system (IS) quality, customer services quality, and product quality. The purpose of this study is to propose an e-banking website quality assessment methodology based on an integrated fuzzy AHP-ELECTRE approach. The fuzzy set theory has been developed for dealing with the problems arising from the vagueness, ambiguity, and subjectivity of human judgment. In the proposed methodology, the weights of the criteria are generated by a fuzzy AHP analysis. Next, fuzzy ELECTRE is used to assess the quality levels of the websites. In the third step, a fuzzy dominance relation approach is used to rank the alternatives. In order to show the potentials of the proposed method, a case study in Turkish banking sector is reported together with a sensitivity analysis. Santrauka Mažmeninės e-bankininkystės sėkmė priklauso nuo klientų aptarnavimo kokybės tinklapyje. Taigi, tinklapio kokybės stebėjimas ir vertinimas yra svarbi sąlyga e-bankininkystės pelningumui. Tinklapio kokybės nustatymas yra daugiadimensis uždavinys, kuris apima informacinės sistemos, klientų aptarnavimo ir produktų kokybę. šio tyrimo tikslas – pasiūlyti e-bankininkystės tinklapio vertinimo metodiką, paremtą integruotu neapibrežtųjų aibių AHP-ELECTRE metodu. Neapibrežtųjų aibių teorija buvo sukurta tam, kad spręsti subjektyvaus žmogiško vertinimo problemą. Siūlomoje metodikoje rodiklių reikšāmin- gumai apskaičiuojami neapibrežtųjų aibių AHP metodu, po to ELECTRE metodu ivertinamas tinklapių kokybės lygis. Toliau, taikant neapibrežtųjų aibių dominavimo teoriją, surikiuojamos alternatyvos. Metodo tinkamumas demonstruojamas atliekant Turkijos bankininkystės sektoriaus tyrimą ir jautrumo analizę. Reikšminiai žodžiai: daugiakriterinis vertinimas, e-bankininkystė, tinklapio kokybė, AHP, ELECTRE, neapibrežtų aibių dominavimo teorija

This paper proposes a fuzzy multi‐period newsvendor model with pre‐season extension for innovative products. The demand of the product is represented by fuzzy numbers with triangular membership function. The holding and shortage cost parameters are considered as imprecise and also represented by triangular fuzzy numbers. As the selling season draws closer, suppliers lead times shortens and thus production costs increase. In contrast, caused by the oncoming selling season, demand fuzziness decreases and more accurate demand forecasts can be maintained that lead to lower overage/underage costs. The objective of the model is to find the best order period and the best order quantity that will minimize the fuzzy expected total cost. The model is experimented with an illustrative example and supported by sensitivity analyses. Santrauka Straipsnyje pasiūlytas neraiškusis keliu laikotarpiu pardavimo modelis, papildytas paruošiamuoju laikotarpiu inovatyviems produktams. Produkto paklausa apibūdinama neraiškiaisiais skaičiais, aprašytais trikampe priklausomumo funkcija. Turto ir sanaudu parametrai laikomi netiksliais ir taip pat apibūdinami trikampe priklausomumo funkcija aprašytais neraiškiaisiais skaičiais. Kai pardavimo laikotarpis priarteja, tiekimo laikas trumpeja, o gaminio kaina išauga. Priešingai, del praeinančio pardavimo laikotarpio paklausos neapibrežtumas sumažeja ir galima tiksliau prognozuoti paklausa, o tai padeda sumažinti išlaidas del gaminiu pertekliaus ar trūkumo. Šio modelio tikslas – rasti geriausia užsakymo laika ir geriausia užsakymo kieki, kurie padetu sumažinti visu numatomu sanaudu neapibrežtuma. Pateikiamas modelio taikymo pavyzdys ir modelio jautrumo analize. First Published Online: 10 Feb 2011 Reikšminiai žodžiai: atsargu problema, neraiškusis modeliavimas, pardavimas, inovatyvus produktas, neraiškioji paklausa, neraiškioji atsargu savikaina, paruošiamasis laikotarpis

Selecting an appropriate six sigma project is one of the most important problems for a manufacturing company because it impacts the manufacturing costs. Besides, an appropriate choice of Six Sigma projects is very important as it helps to improve quality, reduce variation, and eliminate waste of a manufacturing system. Therefore, the main purpose of this study is to provide a good insight into the use of an integrated decision-making methodology in the evaluation of Six Sigma projects. For this purpose, we integrate three multi-criteria decision-making (MCDM) methods by applying a modified Delphi method, Analytical Hierarchy Process (AHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) methodologies. After the evaluation criteria of Six Sigma projects are determined by a Modified Delphi method, the weights of criteria are calculated by applying the AHP method. The FTOPSIS method is then employed to achieve the final ranking results. A real case application along with a sensitivity analysis is presented to show the effectiveness of the proposed methodology. The research question for this methodology is how we can develop an integrated MCDM model to select six sigma projects.

Supplier selection is a multiattribute decision making (MADM) problem which contains both qualitative and quantitative factors. Supplier selection has vital importance for most companies. The aim of this paper is to provide an AHP based analytical tool for decision support enabling an effective multicriteria supplier selection process in an air conditioner seller firm under fuzziness. In this article, the Analytic Hierarchy Process (AHP) under fuzziness is employed for its permissiveness to use an evaluation scale including linguistic expressions, crisp numerical values, fuzzy numbers and range numerical values. This scale provides a more flexible evaluation compared with the other fuzzy AHP methods. In this study, the modified AHP was used in supplier selection in an air conditioner firm. Three experts evaluated the suppliers according to the proposed model and the most appropriate supplier was selected. The proposed model enables decision makers select the best supplier among supplier firms effectively. We confirm that the modified fuzzy AHP is appropriate for group decision making in supplier selection problems.

Renewable energy is the energy generated from natural resources such as sunlight, wind, rain, tides and geothermal heat. Turkey has a great renewable energy potential with its natural resources such as biomass, geothermal, hydropower, solar, and wind. Selection among energy alternatives is a multicriteria decision-making problem with conflicting and interactive criteria. In this paper, the best energy alternative of Turkey is determined by taking into interactions among criteria by using Choquet integral methodology.

The performance of a product depends on if it is created in terms of expected functional requirements. A product is designed to satisfy some certain tasks. In this study, the design of an automobile seat is handled. Automobile seat design procedure is based on experience and trial-and-error method, rather than structured and scientific methods. Axiomatic design is a design theory providing a systematic approach to engineering design. We propose a new product development algorithm based on axiomatic design principles. The independence axiom of axiomatic design is extended to fuzzy environment. Then, an automobile seat design process is taken into consideration by the proposed algorithm. The design characteristics of an automobile seat and their priorities are determined. Moreover, the design dimensions of an automobile seat are defined for Turkish drivers.

In an uncertain economic decision environment, an expert's knowledge about discounting cash flows consists of a lot of vagueness instead of randomness. Cash amounts and interest rates are usually estimated by using educated guesses based on expected values or other statistical techniques to obtain them. Fuzzy numbers can capture the difficulties in estimating these parameters. Fuzziness is one aspect of uncertainty. It is the vagueness found in the definition of a concept or the meaning of a term. Fuzzy memberships represent similarities of objects to imprecisely denned properties, while probabilities convey information about relative frequencies. In this paper, two types of investment analyses are made. First, fuzzy parameters are used in the stochastic investment analysis. Then, another investment analysis is examined by using the concept of probability of a fuzzy event. Santrauka Nepastovioje ekonominių sprendimų aplinkoje eksperto žinios apie diskontuotus pinigų srautus yra daugiau neapibrėžtos nei atsitiktinės. Pinigų srautų dydis ir palūkanų normos paprastai nustatomos remiantis prognozuojamomis tiketinomis vertėmis ar pasitelkiant kitus statistinius metodus. Nustatant šiuos rodiklius, kylančius sunkumus gali padeti sumažinti neapibrežtieji skaičiai. Tačiau neapibrežtumas yra tik vienas iš nepastovumo aspektų. Sudetinga nusakyti šio termino prasmę ir koncepciją. Neapibrežtosios aibės išreiškia netiksliai įvardytas objektu savybės, o tikimybės perteikia informaciją apie santykinius įvykių dažnumus. Šiame straipsnyje atlikta dviejų tipų investicijų analizė. Pirmiausia, atliekant stochastine investicijų analizę, panaudoti neapibrežtųjų aibių elementai. Veliau atlikta investicijų analizė, taikant tikimybinė neapibrežtojo įvykio koncepcija. First published online: 21 Oct 2010 Reikšminiai žodžiai: neapibrežtasis skaičius, neapibrežtasis ivykis, neapibrežtoji tikimybe, investicijos

Traditional valuation methods are less viable under uncertainty. Hence, other methods such as real options valuation models, which can minimize uncertainty, have become more important. In this study, the hybrid approach suggested by Carlsson and Fuller is examined for the case of discrete compounding as this approach better models risky cash flows. A new real options valuation model that will evaluate the investment in a more realistic way is suggested by postponing the defuzzification of parameters in early stages. The suggested model has been applied to the data of an oil field investment and in conclusion the loss of information caused by early‐defuzzification has been determined. Santrauka Tradiciniai vertinimo metodai yra mažiau patikimi esant neapibrėžtumams. Vadinasi, kiti metodai, tokie kaip realių pasirinkčių vertinimo modeliai, kurie gali minimizuoti neapibrėžtumus, tampa svarbesni. Šiame straipsnyje nagrinėjamas hibridinis Carlsson ir Fuller metodas, kuris buvo panaudotas diskrečiajam rizikingų pinigų srautų modeliavimui. Pasiūlytas naujas realių pasirinkčių vertinimo modelis, kuris realistiškiau įvertins investicijas, rodiklius apibūdinančią neapibrėžtą informaciją apdorojant ankstyvojoje stadijoje. Pasiūlytas modelis buvo pritaikytas investicijoms į naftos verslą modeliuoti, nustatytas informacijos nuostolis, kuris atsiranda dėl ankstyvo neapibrėžtų duomenų apdorojimo. First published online: 21 Oct 2010 Reikšminiai žodžiai: neapibrėžtos aibės, realių pasirinkčių vertinimas, neapibrėžtos pasirinktys, investavimas.

In the process of fuzzy decision-making, ranking of fuzzy numbers is a necessity. The types of fuzzy numbers are triangular, trapezoidal, and L-R type. In the literature, there are many methods developed for ranking fuzzy numbers. These methods may produce different ranking results. Many of these methods necessitate graphical representations, complex and tedious calculations. The method developed in this paper has some advantages with respect to the other methods in both graphical representations and calculations. Applicability of the proposed method to multi-criteria decision-making methods, i.e. fuzzy scoring, fuzzy AHP and fuzzy TOPSIS methods, is shown in the paper.

In this paper a new artificial immune system (AIS) algorithm is proposed to solve multi objective fuzzy flow shop scheduling problems. A new mutation operator is also described for this AIS. Fuzzy sets are used to model processing times and due dates. The objectives are to minimize the average tardiness and the number of tardy jobs. The developed new AIS algorithm is tested on real world data collected at an engine cylinder liner manufacturing process. The feasibility and effectiveness of the proposed AIS is demonstrated by comparing it with genetic algorithms. Computational results demonstrate that the proposed AIS algorithm is more effective meta-heuristic for multi objective flow shop scheduling problems with fuzzy processing time and due date.

This paper addresses the Hybrid Flow Shop (HFS) scheduling problems to minimize the makespan value. In recent years, much attention is given to heuristic and search techniques. Genetic algorithms (GAs) are also known as efficient heuristic and search techniques. This paper proposes an efficient genetic algorithm for hybrid flow shop scheduling problems. The proposed algorithm is tested by Carlier and Neron’s (2000) benchmark problem from the literature. The computational results indicate that the proposed efficient genetic algorithm approach is effective in terms of reduced total completion time or makespan (Cmax) for HFS problems.