Browsing by Author "Samanlioglu,F."

Now showing 1 - 4 of 4

Citation Count: 25
Fuzzy Ahp-Gra Approach To Evaluating Energy Sources: a Case of Turkey
(Emerald Group Holdings Ltd., 2020) Ayağ,Z.; Samanlioglu,F.
Purpose: Since the demand for energy has dramatically increased in the countries which have fast-growing population and economy, they have faced with a critical problem of how to evaluate a set of potential energy sources (i.e. nuclear, natural gas, bio, geothermal, hydro, wind and solar) and choose the ultimate energy source for their needs. On the other hand, this critical problem turns into a multiple-criteria decision-making (MCDM) in the presence of a set of energy source alternatives and evaluation criteria. In literature, there are many MCDM methods introduced to solve for different kinds of problems. The purpose of this paper is to present an integrated approach for evaluating energy sources using fuzzy AHP and GRA, with a case for Turkey. Design/methodology/approach: In this paper, the analytic hierarchy process (AHP) and grey relational analysis (GRA) methods are used because of their advantages for similar problems. On the other hand, due to the fact that the conventional AHP by a nine-point scale and GRA method using a scale with crisp values can be unable to handle to capture the right judgments of a decision-maker(s), to reflect the vagueness and uncertainty on the judgments of a decision-maker, the fuzzy logic is integrated with the AHP and GRA. Findings: The contributions of the paper to the literature are given in two dimensions as follows: it presents an integrated approach for complex decision processes with subjective data or vague information; the proposed approach, the fuzzy AHP-GRA method for energy source selection, is unique for the related problem in literature. The results of the proposed model from the case of Turkey will help practitioners and experts of how to apply it to the similar problems in the field of energy management. Research limitations/implications: In short, in this paper, an integrated approach is proposed through the fuzzy AHP and the fuzzy GRA methods. As the fuzzy AHP is used to determine the weights of evaluation criteria, the fuzzy GRA is used to rank energy source alternatives. Practical implications: In addition, a case study for Turkey is presented to show the applicability of the proposed approach for potential practitioners who are authority in the field of energy in public and private sectors. Social implications: On the other hand, the proposed approach, the fuzzy AHP-GRA for energy source selection can also be an intelligent tool for public and private energy companies in Turkey, as well as others in the world. Originality/value: On the other hand, in this paper, to the best of the authors’ knowledge, the study contributes to the literature that the first time, they use the fuzzy alpha-cut AHP and GRA in fuzzy environment for energy source evaluation problem. © 2019, Emerald Publishing Limited.
Citation Count: 0
Knitting Machine Selection for a Textile Company in Turkey with F-AHP-PROMETHEE II
(Institute of Industrial and Systems Engineers, IISE, 2023) Samanlioglu,F.; Aday,Ş.; Sağıroğlu,M.; Çelik,C.; Bektaş,A.Y.
Global competition and fast development of technologies force textile companies to select and purchase efficient machines to maintain their place among competitors. Selection of a knitting machine for a textile company requires a multi-criteria decision making (MCDM) process since several possibly contradictory quantitative and qualitative criteria needs to be considered by the decision makers. In this study, as the MCDM method, “fuzzy Analytic Hierarchy Process” (F-AHP) and “fuzzy Preference Ranking Organization Method for Enrichment Evaluation” (F-PROMETHEE II) methods are integrated (F-AHP-PROMETHEE II) in order to gain from both methods’ benefits. In F-AHP-PROMETHEE II, first, F-AHP is applied to establish the importance weights of criteria and then F-PROMETHEE II is implemented to rank knitting machine alternatives employing the determined weights. A case study is given, where 3 knitting machine alternatives determined by a textile company in Turkey (Uğur Konfeksiyon San. ve Tic. A.Ş) are evaluated based on 10 criteria with the help of 3 company managers acting as decision makers. © IISE and Expo 2023.All rights reserved.
Citation Count: 66
A Memetic Random-Key Genetic Algorithm for a Symmetric Multi-Objective Traveling Salesman Problem
(2008) Samanlioglu,F.; Ferrell,Jr. W.G.; Kurz,M.E.
This paper proposes a methodology to find weakly Pareto optimal solutions to a symmetric multi-objective traveling salesman problem using a memetic random-key genetic algorithm that has been augmented by a 2-opt local search. The methodology uses a "target-vector approach" in which the evaluation function is a weighted Tchebycheff metric with an ideal point and the local search is randomly guided by either a weighted sum of the objectives or a weighted Tchebycheff metric. The memetic algorithm has several advantages including the fact that the random keys representation ensures that feasible tours are maintained during the application of genetic operators. To illustrate the quality of the methodology, experiments are conducted using Euclidean TSP examples and a comparison is made to one example found in the literature. © 2008 Elsevier Ltd. All rights reserved.
Citation Count: 7
On the Uniqueness of Epidemic Models Fitting a Normalized Curve of Removed Individuals
(Springer Verlag, 2015) Bilge,A.H.; Samanlioglu,F.; Ergonul,O.
The susceptible-infected-removed (SIR) and the susceptible-exposed-infected-removed (SEIR) epidemic models with constant parameters are adequate for describing the time evolution of seasonal diseases for which available data usually consist of fatality reports. The problems associated with the determination of system parameters starts with the inference of the number of removed individuals from fatality data, because the infection to death period may depend on health care factors. Then, one encounters numerical sensitivity problems for the determination of the system parameters from a correct but noisy representative of the number of removed individuals. Finally as the available data is necessarily a normalized one, the models fitting this data may not be unique. We prove that the parameters of the (SEIR) model cannot be determined from the knowledge of a normalized curve of “Removed” individuals and we show that the proportion of removed individuals, R(t), is invariant under the interchange of the incubation and infection periods and corresponding scalings of the contact rate. On the other hand we prove that the SIR model fitting a normalized curve of removed individuals is unique and we give an implicit relation for the system parameters in terms of the values of (Formula presented.) and (Formula presented.), where Rf is the steady state value of R(t) and Rm and (Formula presented.) are the values of R(t) and its derivative at the inflection point tm of R(t). We use these implicit relations to provide a robust method for the estimation of the system parameters and we apply this procedure to the fatality data for the H1N1 epidemic in the Czech Republic during 2009. We finally discuss the inference of the number of removed individuals from observational data, using a clinical survey conducted at major hospitals in Istanbul, Turkey, during 2009 H1N1 epidemic. © 2014, Springer-Verlag Berlin Heidelberg.