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Öğe AN APPLICATION OF EFFECTIVE GENETIC ALGORITHMS FOR SOLVING HYBRID FLOW SHOP SCHEDULING PROBLEMS(ATLANTIS PRESS, 2008) Kahraman, Cengiz; Engin, Orhan; Kaya, İhsan; Yılmaz, Mustafa KerimThis 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 (C-max) for HFS problems.Öğe Fuzzy Acceptance Sampling and Characteristic Curves(Atlantıs Press, 2012) Turanoğlu, Ebru; Kaya, İhsan; Kahraman, CengizAcceptance 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.Öğe Fuzzy Acceptance Sampling Plans(Springer-Verlag Berlin, 2010) Kahraman, Cengiz; Kaya, İhsanAcceptance sampling is one of the major components of the field of statistical quality control. It is primarily used for the inspection of incoming or outgoing lots. In recent years, it has become typical to work with suppliers to improve their process performance through the use of statistical process control (SPC). Acceptance sampling refers to the application of specific sampling plans to a designated lot or sequence of lots. Acceptance sampling procedures can, however, be used in a program of acceptance control to achieve better quality at lower cost, improved control, and increased productivity. In some cases, it may not be possible to define acceptance sampling parameters as crisp values. Especially in production environments, it may not be easy to define the parameters fraction of nonconforming, acceptance number, or sample size as crisp values. In these cases, these parameters can be expressed by linguistic variables. The fuzzy set theory can be used successfully to cope the vagueness in these linguistic expressions for acceptance sampling. In this paper, the two main distributions of acceptance sampling plans which are binomial and Poisson distributions are handled with fuzzy parameters and their acceptance probability functions are derived. Then fuzzy acceptance sampling plans are derived based on these distributions.Öğe Fuzzy Analytic Hierarchy Process with Type-2 Fuzzy Sets(WORLD SCIENTIFIC PUBL CO PTE LTD, 2012) Kahraman, Cengiz; Sarı, İrem Uçal; Turanoğlu, Ebru; Öztayşi, BaşarThe membership functions of type-1 fuzzy sets have no uncertainty associated with it. While excessive arithmetic operations are needed with type-2 fuzzy sets with respect to type-1’s, type-2 fuzzy sets generalize type-1 fuzzy sets and systems so that more uncertainty for defining membership functions can be handled. A type-2 fuzzy set lets us incorporate the uncertainty of membership functions into the fuzzy set theory. Some fuzzy multicriteria methods have recently been extended by using type-2 fuzzy sets. Analytic Hierarchy Process (AHP) is a widely used multicriteria method that can take into account various and conflicting criteria at the same time. Our objective is to develop an interval type-2 fuzzy AHP method together with a new ranking method for type-2 fuzzy sets. We apply the proposed method to a supplier selection problem.Öğe Fuzzy and Grey Forecasting Techniques and Their Applications in Production Systems(Springer-Verlag Berlin, 2010) Kahraman, Cengiz; Yavuz, Mesut; Kaya, İhsanForecasting is an important part of decision making as many of our decisions are based on predictions of future unknown events. Forecast is an interesting research topic that has received attention from many researchers in the past several decades. Forecasting has many application areas including but not limited to stock markets, futures markets, enrollments of a school, demand of a product and/or service. Management needs to reduce the risks associated with decision-making, which can be done by anticipating the future more clearly. Accurate forecasts are therefore essential for risk reduction. Forecasting provides critical inputs to various manufacturing-related processes, such as production planning, inventory management, capital budgeting, purchasing, work-force scheduling, resource allocation and other important parts of the production system operation. Accurate forecasts are crucial for successful manufacturing and can lead to considerable savings when implemented efficiently. Forecasting literature contains a large variety of techniques from simple regression to complex metaheuristics such as neural networks and genetic algorithms. Fuzzy set theory is also another useful tool to increase forecast efficiency and effectiveness. This chapter summarizes and classifies forecasting techniques based on crisp logic, fuzzy logic and the grey theory. The chapter also presents numerical examples of fuzzy simple linear regression and grey forecasting methodology.Öğe Fuzzy Process Capability Analysis and Applications(Springer-Verlag Berlin, 2010) Kahraman, Cengiz; Kaya, İhsanProcess capability indices (PCIs) are very useful statistical analysis tools to summarize process' dispersion and location through process capability analysis (PCA). PCIs are mainly used in industry to measure the capability of a process to produce products meeting specifications. Traditionally, the specifications are defined as crisp numbers. Sometimes, the specification limits (SLs) can be expressed in linguistic terms. Traditional PCIs cannot be applied for this kind of data. There are also some limitations which prevent a deep and flexible analysis because of the crisp definition of SLs. In this chapter, the fuzzy set theory is used to add more sensitiveness to PCA including more information and flexibility. The fuzzy PCA is developed when the specifications limits are represented by triangular or trapezoidal fuzzy numbers. Crisp SLs with fuzzy normal distribution are used to calculate the fuzzy percentages of conforming (FCIs) and nonconforming (FNCIs) items by taking into account fuzzy process mean, (mu) over tilde and fuzzy variance, (sigma) over tilde (2). Then fuzzy SLs are used together with (mu) over tilde and (sigma) over tilde (2) to produce fuzzy PCIs (FPCIs). FPCIs are analyzed under the existence of correlation and thus fuzzy robust process capability indices are obtained. Then FPCIs are improved for six sigma approach. And additionally, process accuracy index is analyzed under fuzzy environment. The results show that fuzzy estimations of PCIs have much more treasure to evaluate the process when it is compared with the crisp case.Öğe Group Decision Making for Advanced Manufacturing Technology Selection Using the Choquet Integral(IGI GLOBAL, 2013) Kahraman, Cengiz; Cebi, Selcuk; Kaya, IhsanAdvanced manufacturing technology (AMT) is defined as a modern method of production incorporating highly automated and sophisticated computerized design and operational systems. Hence, an investment decision to adopt AMT is a strategic decision. A group decision making process is stressful when group members have different views under multiple and conflicting criteria. Satisfying group members' opinions has a critical impact on a decision. In this chapter, a multiple criteria group decision making problem under a fuzzy environment is used for the selection among AMTs. Choquet integral methodology is used for this selection. A strategic investment problem of a company for a suitable Automated Storage/Retrieval System (AS/RS) is considered and discussed.Öğe A Hierarchy Grey Relational Analysis for Selecting the Renewable Electricity Generation Technologies(INT ASSOC ENGINEERS-IAENG, 2011) Sarucan, Ahmet; Baysal, Mehmet Emin; Kahraman, Cengiz; Engin, OrhanEnergy resources are classified as renewable and non-renewable in general. Non renewable energy resources have been exhausted gradually. Renewable energy resources such as wind power, hydropower, geothermal power, solar power and photovoltaic power have importance more than ever before. But, researchers are looking for selections of renewable electricity generation as it is a technological problem. This problem is a multi-criteria decision making problem. One of the solution methods for this problem is a combination of the analytic hierarchy process (AHP) and the grey relational analysis (GRA). Hierarchical GRA method is based on grey system theory. In this study, a new approach to the selection of renewable electricity generation is prepared using multi-criteria decision making method. The hierarchical GRA frame work uses three criteria and sub-criteria from which it possible to evaluate to different renewable electricity generation technologies. This application is a novel approach for the selection of renewable electricity generation technologies.Öğe Information systems outsourcing decisions using a group decision-making approach(PERGAMON-ELSEVIER SCIENCE LTD, 2009) Kahraman, Cengiz; Engin, Orhan; Kabak, Özgür; Kaya, İhsanOutsourcing refers to a company that contracts with another company to provide services that might otherwise be performed by in-house employees. Information system (IS) outsourcing policies define the criteria that organizations utilize to decide upon the scope and degree of reliance of their IS capabilities upon external sources. IS outsourcing is an innovative organizational tool for IS management in both private and public sector organizations. In this paper, an interactive group decision-making methodology is proposed to select/rank 15 providers under multiple criteria. A measure for the consensus level of the group preferences is developed to satisfy an acceptable level of group agreement and reliability. The Spearman coefficients for both the aggregated rank order and each DM's rank order have also been calculated. The group and the individual evaluations are gathered through a fuzzy TOPSIS approach. The proposed methodology is applied in the largest office furniture manufacturer in Konya-Turkey. Eight alternative IS providers are evaluated based on seven criteria by five decision makers. Sensitivity analyses are also provided to see the effects of parameter changes on the final decision. (c) 2008 Elsevier Ltd. All rights reserved.Öğe AN INTEGRATED FUZZY AHP/DEA APPROACH FOR PERFORMANCE EVALUATION OF TERRITORIAL UNITS IN TURKEY(VILNIUS GEDIMINAS TECH UNIV, 2018) Calik, Ahmet; Yapici Pehlivan, Nimet; Kahraman, CengizDue 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.Öğe Multiprocessor Task Scheduling in Multistage Hybrid Flow-Shops: A Parallel Greedy Algorithm Approach(ELSEVIER, 2010) Kahraman, Cengiz; Engin, Orhan; Kaya, İhsan; Öztürk, R. ElifHybrid flow shop scheduling problems have a special structure combining some elements of both the flow shop and the parallel machine scheduling problems. Multiprocessor task scheduling problem can be stated as finding a schedule for a general task graph to execute on a multiprocessor system so that the schedule length can be minimized. Hybrid Flow Shop Scheduling with Multiprocessor Task (HFSMT) problem is known to be NP-hard. In this study we present an effective parallel greedy algorithm to solve HFSMT problem. Parallel greedy algorithm (PGA) is applied by two phases iteratively, called destruction and construction. Four constructive heuristic methods are proposed to solve HFSMT problems. A preliminary test is performed to set the best values of control parameters, namely population size, subgroups number, and iteration number. The best values of control parameters and operators are determined by a full factorial experimental design using our PGA program. Computational results are compared with the earlier works of Oguz et al. [1,3], and Oguz [2]. The results indicate that the proposed parallel greedy algorithm approach is very effective in terms of reduced total completion time or makespan (C-max) for the attempted problems.Öğe A New Artificial Immune System Algorithm for Multiobjective Fuzzy Flow Shop Problems(ATLANTIS PRESS, 2009) Kahraman, Cengiz; Engin, Orhan; Yılmaz, Mustafa KerimIn 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.Öğe A New Artificial Immune System Algorithm for Multiobjective Fuzzy Flow Shop Problems(2009) Kahraman, Cengiz; Engin, Orhan; Yılmaz, Mustafa KerimIn 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.Öğe Organizational Strategy Development in Distribution Channel Management Using Fuzzy AHP and Hierarchical Fuzzy Topsis(PERGAMON-ELSEVIER SCIENCE LTD, 2012) Paksoy, Turan; Pehlivan Yapıcı, Nimet; Kahraman, CengizDistribution channel management not only consists of choosing distribution channels. In fact, probably the most difficult phase of the distribution management starts after this choice. Determining an appropriate organization strategy for distribution channel management is like a problem of concern to marketing practitioners and academics as well in this phase. In this study, the organization strategy of distribution channel management is developed using fuzzy analytic hierarchy process (FAHP) and hierarchical fuzzy TOPSIS (HFTOPSIS) for an edible-vegetable oils manufacturer firm operating in Turkey. The company distributes its products all over the country. Due to the complex structure of the distribution network, the company wants to decide the organization strategy to manage the distribution channels. In this paper, the methods of FAHP and HFTOPSIS for evaluating and selecting among the five organization strategy models for distribution channel management of vegetable oil manufacturer have been presented. The proposed models include determinants of distribution channel management for edible-vegetable oil industry; (i) customer profile, (ii) distributor reliability, (iii) the position of competitors in market, and (iv) managerial and financial perspective. Using FAHP and HFTOPSIS, hybrid based strategy (KBS), which has the greatest desirability index value after the evaluation among the five alternatives is found as the best choice. Thus, the case of the vegetable oil manufacturer company provides the researchers and practitioners to understand in a better way the importance of developing organization strategy in channel management from a practical point of view.Öğe Process capability analyses based on fuzzy measurements and fuzzy control charts(PERGAMON-ELSEVIER SCIENCE LTD, 2011) Kaya, Ihsan; Kahraman, CengizProcess performance can be analyzed by using process capability indices (PCIs), which are summary statistics to depict the process location and dispersion successfully. Although they are very usable statistics, they have some limitations which prevent a deep and flexible analysis because of the crisp measurements and specification limits (SLs). If the specification limits or measurements are expressed by linguistic variables, traditional PCIs cause some misleading results. In this paper, the fuzzy set theory is used to add more information and flexibility to process capability analyses (PCA). For this aim, linguistic definition of the quality characteristic measurements are converted to fuzzy numbers and fuzzy PCIs are produced based on these measurements and fuzzy specification limits (SLs). Also fuzzy control charts are derived for fuzzy measurements of the related quality characteristic. They are used to increase the accuracy of PCA by determining whether or not the process is in statistical control. The fuzzy formulation of the indices C-p and C-pk, which are the most used two traditional PCIs, are produced when SLs and measurements are both triangular (TFN) and trapezoidal fuzzy numbers (TrFN). The proposed methodologies are applied in a piston manufacturer in Konya's Industrial Area, Turkey. (C) 2010 Elsevier Ltd. All rights reserved.Öğe Renewable Energy System Selection Based on Computing With Words(Atlantis Press, 2010) Kahraman, Cengiz; Kaya, İhsan; Çebi, SelçukRenewable 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.Öğe A Scatter Search Method for Fuzzy Job Shop Scheduling Problem with Availability Constraints(INT ASSOC ENGINEERS-IAENG, 2011) Engin, Orhan; Yılmaz, Mustafa Kerim; Kahraman, Cengiz; Baysal, Mehmet Emin; Sarucan, AhmetIn the last decade job shop scheduling problems have been subject to intensive research due to their multiple applications. Job shop scheduling is known as a strongly NP-complete problem. In the job shop scheduling problems, processing times and due dates are very dynamically due to both human and machine resource factors. Fuzzy sets are used to model the uncertain processing times and due dates in recent years. In this study, a fuzzy job shop scheduling problem with availability constraints is considered. A Scatter Search (SS) method is proposed to solve these problems. The feasibility and effectiveness of the proposed scatter search method is demonstrated by comparing it with the hybrid genetic algorithm (HGA).Öğe A Scatter Search Method for Multiobjective Fuzzy Permutation Flow Shop Scheduling Problem: A Real World Application(SPRINGER, 2009) Engin, Orhan; Kahraman, Cengiz; Yılmaz, Mustafa KerimIn this chapter, a scatter search (SS) method is proposed to solve the multiobjective permutation fuzzy flow shop scheduling problem. The objectives are minimizing the average tardiness and the number of tardy jobs. The developed scatter search method is tested on real-world data collected at an engine piston manufacturing company. Using the proposed SS algorithm, the best set of parameters is used to obtain the optimal or near optimal solutions of multiobjective fuzzy flow shop scheduling problem in the shortest time. These parameters are determined by full factorial design of experiments (DOE). The feasibility and effectiveness of the proposed scatter search method is demonstrated by comparing it with the hybrid genetic algorithm (HGA).Öğe The Selection of Renewable Energy Power Plant Technology Using Fuzzy Data Envelopment Analysis(INT ASSOC ENGINEERS-IAENG, 2011) Baysal, Mehmet Emin; Sarucan, Ahmet; Kahraman, Cengiz; Engin, OrhanThe efficiency of resource utilization and sustainabfiity are rising values all over the world. Power generation technologies have an important weight in this manner for a sustainable future. Particularly, renewable energy power technologies should take over the non-renewable power generation technologies when considered on environmental issues. However it is too far to substitute renewable onto non-renewable as for now. At this point, there is another issue for choosing the best yet suitable alternative technology. The selection problem is a difficult multi-criteria decision making problem in many fields as well as in the selection of power generation technology. This paper proposed a data envelopment analysis model approach by using triangular fuzzy numbers (TFN) as the solution. Six different technologies were used as the decision making units (DMU). Inputs and outputs variables were selected in general indicators such as economical and technical. It was showed that policy and decision makers could follow this methodology to produce effective solution for energy generation problems.Öğe A two phased fuzzy methodology for selection among municipal projects(VILNIUS GEDIMINAS TECH UNIV, 2015) Baysal, Mehmet Emin; Kaya, İhsan; Kahraman, Cengiz; Sarucan, Ahmet; Engin, OrhanA 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.
