Funda Samanlıoğlu

Samanlıoğlu, Funda

Name Variants

SAMANLIOĞLU, Funda
S.,Funda
F. Samanlıoğlu
Funda Samanlıoğlu
FUNDA SAMANLIOĞLU
S., Funda
SAMANLIOĞLU, FUNDA
Samanlıoğlu,F.
Samanlioglu, Funda
Samanlıoğlu, FUNDA
Samanlioglu,Funda
Samanlıoğlu, Funda
Funda, Samanlioglu
Samanlıoğlu, F.
Samanlioglu F.
Funda SAMANLIOĞLU
Samanlioglu,F.

Job Title

Prof. Dr.

Email Address

fsamanlioglu@khas.edu.tr

Main Affiliation

Industrial Engineering

Scholarly Output

50

Articles

37

Citation Count

819

Supervised Theses

4 Scholarly Output Search Results

Now showing 1 - 10 of 50

Citation - WoS: 18
Citation - Scopus: 21
Evaluation of Irrigation Methods in Soke Plain With Hf-Ahp Ii Hybrid Mcdm Method
(Elsevier, 2022) Burak, Selmin; Samanlıoğlu, Funda; Samanlıoğlu, Funda; Ulker, Duygu
Soke Plain (Turkey) is one of the two plains where cotton production is the highest in Turkey, the leading country for cotton production in the Mediterranean Basin. The cropping pattern in Soke Plain is dominated by cotton with a ratio of 97%. The overall irrigation scheme is equipped with conventional systems (i.e., surface, furrow) whose efficiency is approximately 50% due to high evaporation and physical losses. Water efficiency improve-ment in cotton irrigation necessitates a thorough evaluation of the agricultural water management for Soke Plain, a water-scarce region under drought threat. In this paper, a hybrid multi-criteria decision making (MCDM) method is presented for the evaluation and selection of irrigation methods. This process involves various potentially conflicting qualitative and quantitative criteria, therefore, a hybrid MCDM method such as HF-AHP-PROMETHEE II is needed to make decisions. In HF-AHP-PROMETHEE II, Hesitant Fuzzy Analytic Hierarchy Process (HF-AHP) is first implemented to determine importance weights of criteria and then Hesitant Fuzzy Preference Ranking Organization Method for Enriching Evaluations II (HF-PROMETHEE II) is utilized to assess and rank the irrigation method alternatives. For comparison analysis, HF-AHP-TOPSIS (HF-AHP-Technique for Order Preference by Similarity to Ideal Solution) method is also implemented to the same problem. A case study is presented where five irrigation method alternatives in Soke Plain are assessed by five expert decision-makers (DMs), based on fifteen evaluation criteria. Sprinkler is found to be the first ranked irrigation method among five alternatives with both HF-AHP-PROMETHEE II and HF-AHP-TOPSIS resulting in the same ranking. The selection of this irrigation technique by the expert DMs is compliant with prevailing regional features related to hydro-logic, climatic, environmental conditions and with regard to cotton, one of the highest water-consuming crops.
Analysis of the Stochastic Skiving Stock Problem
(Kadir Has Üniversitesi, 2022-04) KARACA, TOLGA KUDRET; Samanlıoğlu, Funda; Samanlıoğlu, Funda
This study addresses the stochastic version of the one-dimensional skiving stock problem (SSP), a rather recent combinatorial optimization challenge. The tradi tional SSP aims to determine the optimal structure that skives (combines) small items of various sizes side-by-side to form as many large items (products) as possible that satisfy a target width. This study considers a single-product and multi-product cases for the stochastic SSP. First, two-stage stochastic programming model is pre sented to minimize the total cost for the single product stochastic SSP which is under random demand. Integration of the Column Generation, Progressive Hedging Al gorithm, and Branch and Bound is proposed where Progressive Hedging Algorithm is embedded in each node of the search tree to obtain the optimal integer solution. Next, the single product stochastic model is extended to the multi-product, multi random variable model with the additional costs as a large size complex model. To examine this large-sized stochastic N P-hard problem, a two-stage stochastic programming approach is implemented. Moreover, as a solution methodology, this problem is handled in two phases. In the first phase, the Dragonfly Algorithm constructs minimal patterns as an input for the next phase. The second phase executes a Sample Average Approximation method that provides solutions for the stochastic production problem with large size scenarios. Results indicate that the two-phase heuristic approach provides good feasible solutions under numerous sce narios without requiring excessive execution time. Finally, a multi-objective case for the deterministic SSP is analyzed where the objectives are minimization of the trim loss (waste), number of items in each product by considering the quality aspect, and number of pattern changes as the set-up. Lexicographic method is preferred for the multi-objective approach where preferences are ranked according to their importance. Column generation and Integer programming are further used to solve the multi-objective problem. In addition, a heuristic is proposed for the same multi objective problem.
Citation - WoS: 17
Citation - Scopus: 20
An Intelligent Approach To Supplier Evaluation in Automotive Sector
(Springer, 2016) Ayağ, Zeki; Samanlıoğlu, Funda; Samanlıoğlu, Funda; Ayağ, Zeki
During the process of supplier evaluation selecting the best desirable supplier is one of the most critical problems of companies since improperly selected suppliers may cause losing time cost and market share of a company. For this multiple-criteria decision making selection problem in this paper a fuzzy extension of analytic network process (ANP) which uses uncertain human preferences as input information in the decision-making process is applied since conventional methods such as analytic hierarchy process cannot accommodate the variety of interactions dependencies and feedback between higher and lower level elements. The resulting fuzzy ANP enhances the potential of the conventional ANP for dealing with imprecise and uncertain human comparison judgments. In short in this paper an intelligent approach to supplier selection problem through fuzzy ANP is proposed by taking into consideration quantitative and qualitative elements to evaluate supplier alternatives and a case study in automotive sector is presented.
Citation - WoS: 2
Citation - Scopus: 2
Solution approaches for the bi-objective Skiving Stock Problem
(Pergamon-Elsevier Science Ltd, 2023) Samanlıoğlu, Funda; Samanlıoğlu, Funda; Altay, Ayca
The Skiving Stock Problem (SSP) aims to determine an optimal plan for producing as many large objects as possible by combining small items. The skiving process may need different considerations depending on the production environment and the product characteristics. In this study, we address bi-objective 1D-SSP with two conflicting objectives. One common objective is to minimize the trim loss remaining after skiving, as removing the excess width is an extra procedure. When welding is an element of the skiving process, increasing the number of items for each product indicates compromised quality. Therefore, minimizing the number of small items for each product becomes a primary objective in such cases. To solve this bi-objective version of the NP-hard problem, we implement a Lexicographic Method (LM) in which the importance of the objectives imposes their preference orders. We propose two methodologies within the LM framework. The first methodology integrates Column Generation (CG) and Branch & Bound (B&B) to search for an exact solution. Given the excessive computational time an exact solver may require for tight or large-sized problems, we propose a heuristic method integrating the Dragonfly Algorithm (DA) and a Constructive Heuristic (CH). Real-world application results validate the exact solver and demonstrate comparable results for the heuristic solver in terms of solution quality and computational time. The efficiency of the solution methodologies for a preemptive multi-objective SSP aims to support decision-makers with make-or-buy decisions.
Citation - Scopus: 3
Determining Master Schedule of Surgical Operations by Integer Programming: a Case Study
(Institute of Industrial Engineers, 2010) Samanlıoğlu, Funda; Samanlıoğlu, Funda; Ayağ, Zeki; Ayağ, Zeki; Batili, Burcin; Evcimen, Esra; Yılmaz, Gulsah; Atalay, Ozlem
Fixed amounts of available Operating Room (OR) time compatibility of ORs and restrictions related to surgery equipment and surgeon availabilities complicate the process of preparing the master surgical schedule at hospitals. In this research an integer programming model and its application at Etiler World Eye Hospital (in Turkey) are presented in order to create a master surgical schedule that includes the most common surgery types on weekly basis and resolves surgeon equipment and operating room restriction and availability issues. The integer programming model utilizes the available OR time at the hospital by minimizing the total underallocation of OR time with respect to targeted OR time of surgeons taking into consideration surgeon equipment and OR restrictions and availabilities. The mathematical model is then solved using a commercial solver to obtain a weekly master surgical schedule for the hospital.
Citation - Scopus: 0
A Network Model for the Location-Routing Decisions of a Logistics Company
(Institute of Industrial Engineers, 2012) Sama, Funda; Samanlıoğlu, Funda; Yücekaya, Ahmet; Ayağ, Zeki; Ayağ, Zeki; Yücekaya, Ahmet Deniz
In this paper, part of the logistics network of one of the leading logistics companies in Turkey is analyzed. Data related to the candidate warehouse locations, supplies and demands of customers are collected. A network model is developed in order to reconfigure the logistics network. The aim of the mathematical model is to help decision makers decide on the locations of warehouses, as well as routing products from suppliers to the distribution center; from distribution center to warehouses; and finally from warehouses to customers. The mathematical model is solved optimally with LINGO solver, and the comparison of the current network with the optimal solution revealed that the overall operating costs can be reduced by approximately 7%.
Citation - WoS: 40
Citation - Scopus: 42
Computing Trade-Offs in Robust Design: Perspectives of the Mean Squared Error
(Pergamon-Elsevier Science Ltd, 2011) Shin, Sangmun; Samanlıoğlu, Funda; Samanlıoğlu, Funda; Cho, Byung Rae; Wiecek, Margaret M.
Researchers often identify robust design as one of the most effective engineering design methods for continuous quality improvement. When more than one quality characteristic is considered an important question is how to trade off robust design solutions. In this paper we consider a bi-objective robust design problem for which Pareto solutions of two quality characteristics need to be obtained. In practical robust design applications a second-order polynomial model is adequate to accommodate the curvature of process mean and variance functions thus mean-squared robust design models frequently used by many researchers would contain fourth-order terms. Consequently the associated Pareto frontier might be non-convex and supported and non-supported efficient solutions needs to be generated. So the objective of this paper is to develop a lexicographic weighted-Tchebycheff based bi-objective robust design model to generate the associated Pareto frontier. Our numerical example clearly shows the advantages of this model over frequently used weighted-sums model. (C) 2010 Elsevier Ltd. All rights reserved.
Citation - WoS: 6
Citation - Scopus: 10
An Intelligent Approach for the Evaluation of Transformers in a Power Distribution Project
(IOS Press BV, 2020) Samanlıoğlu, Funda; Samanlıoğlu, Funda; Ayağ, Zeki; Ayağ, Zeki
In this study, a hybrid approach is presented for the evaluation and selection of transformers in a power distribution project. Ranking transformers and selecting the best among alternatives is a complex multiple criteria decision making (MCDM) problem with various possibly conflicting quantitative and qualitative criteria. In this research, two hesitant fuzzy MCDM methods; hesitant fuzzy Analytic Hierarchy Process (hesitant F-AHP) and hesitant fuzzy Preference Ranking Organization Method for Enriching Evaluations II (hesitant F-PROMETHEE II) are combined to evaluate and rank transformers. In the hesitant fuzzy AHP-PROMETHEE II, hesitant F-AHP is implemented to determine criteria weights and hesitant F-PROMETHEE II is applied to rank transformer alternatives, utilizing obtained criteria weights. An illustrative example is presented to demonstrate the effectiveness and applicability of the proposed approach. In the example, five transformers are evaluated based on twelve criteria by three decision makers (DMs) and best alternative is selected. For comparison analysis, integration of hesitant F-AHP and hesitant fuzzy Technique for Order Preference by Similarity to Ideal Solution (hesitant F-TOPSIS) is used and results are compared.
Citation - WoS: 9
Citation - Scopus: 11
An Integrated Fuzzy Best-Worst Method for Evaluation of Hotel Website and Digital Solutions Provider Firms
(Hindawi Limited, 2020) Samanlıoğlu, Funda; Samanlıoğlu, Funda; Burnaz, Ayşe Nur; Diş, Berke; Tabaş, Mehmet Doğukan; Adıgüzel, Mehmet
In todays world where technology is rapidly evolving, hotels need to be the best in all conditions to be one step ahead of other competitors. Digital marketing and hotel website solutions play a lead role in this competition. Therefore, hotel websites need to be innovative, user-friendly, and descriptive. The main purpose of the study is to evaluate and rank potential hotel websites and digital solutions provider firms. Since there are various potentially competing quantitative and qualitative criteria to take into consideration in the decision-making process, a multicriteria decision-making (MCDM) method is needed. As the MCDM method, fuzzy best-worst method (FBWM) is integrated with the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS). In this integration, FBWM is applied to determine fuzzy evaluation criteria weights and then F-TOPSIS is implemented to rank alternatives utilizing the obtained fuzzy weights. A case study is presented, where 4 alternative hotel websites and digital solutions provider firms for Paloma Hotels in Turkey are evaluated based on 9 criteria by 3 hotel managers.
Citation - Scopus: 69
A Memetic Random-Key Genetic Algorithm for a Symmetric Multi-Objective Traveling Salesman Problem
(2008) Samanlioglu,F.; Samanlıoğlu, Funda; 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.