Samanlıoğlu, Funda
Loading...
Profile URL
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.
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
Main Affiliation
Industrial Engineering
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
2
ZERO HUNGER
2
Research Products
3
GOOD HEALTH AND WELL-BEING
8
Research Products
6
CLEAN WATER AND SANITATION
2
Research Products
7
AFFORDABLE AND CLEAN ENERGY
3
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
4
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
6
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
2
Research Products
13
CLIMATE ACTION
1
Research Products
17
PARTNERSHIPS FOR THE GOALS
1
Research Products
Documents
54
Citations
1199
h-index
18
Documents
0
Citations
0
Scholarly Output
51
Articles
38
Views / Downloads
300/4334
Supervised MSc Theses
3
Supervised PhD Theses
1
WoS Citation Count
948
Scopus Citation Count
1283
WoS h-index
16
Scopus h-index
18
Patents
0
Projects
0
WoS Citations per Publication
18.59
Scopus Citations per Publication
25.16
Open Access Source
21
Supervised Theses
4
Google Analytics Visitor Traffic
| Journal | Count |
|---|---|
| Journal of Intelligent & Fuzzy Systems | 5 |
| Applied Computational Intelligence and Soft Computing | 3 |
| Journal of Healthcare Engineering | 3 |
| Journal of Mathematical Biology | 2 |
| Agricultural Water Management | 2 |
Current Page: 1 / 6
Scopus Quartile Distribution
Competency Cloud
Scholarly Output Search Results
Now showing 1 - 10 of 51
Article Citation - WoS: 2Citation - Scopus: 2Efficient Approaches for Furnace Loading of Cylindrical Parts(Elsevier Science Inc, 2014) Osman, Mojahid Saeed; Ram, Bala; Samanlıoğlu, FundaThis paper addresses the heat treatment operation in a manufacturing plant that produces different types of cylindrical parts. The immediate prior process to heat treatment is furnace-loading where parts are loaded into baskets. The furnace-loading process is complex and involves issues relating to geometry and heterogeneity in the parts and in their processing requirements. Currently furnace-loading is accomplished by operator ingenuity ; consequently the parts loaded in heat treatment often do not use furnace capacity adequately. Efficiency in furnace operation can be achieved by improving basket utilization which is determined by the furnace-loading process. This paper describes the development of integer and mixed integer LP models for 3D loading of cylindrical parts into furnace baskets. The models consider the exact location of parts to be loaded on the basket and incorporate three models with different objectives ; the first addresses the nesting of parts within one another the second addresses the number of basket layers used and the third addresses the number of baskets used. (C) 2013 Elsevier Inc. All rights reserved.Doctoral Thesis Analysis of the Stochastic Skiving Stock Problem(Kadir Has Üniversitesi, 2022) KARACA, TOLGA KUDRET; Samanlıoğlu, FundaThis 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.Article Citation - WoS: 4Citation - Scopus: 5Solution approaches for the bi-objective Skiving Stock Problem(Pergamon-Elsevier Science Ltd, 2023) Karaca, Tolga Kudret; Samanlıoğlu, Funda; Altay, AycaThe 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.Article Citation - WoS: 16Citation - Scopus: 18An Intelligent Approach for the Evaluation of Innovation Projects(IOS Press, 2020) Samanlıoğlu, Funda; Ayağ, ZekiIn this study, an intelligent approach is presented for the evaluation and selection of innovation projects. Selecting the best innovation project is a complicated multiple criteria decision making (MCDM) problem with several potentially competing quantitative and qualitative criteria. In this paper, two hesitant fuzzy MCDM methods; hesitant fuzzy Analytic Hierarchy Process (hesitant F-AHP) and hesitant fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (hesitant F-VIKOR) are integrated to evaluate and rank innovation projects. In the hesitant fuzzy AHP-VIKOR, hesitant F-AHP is used to find fuzzy evaluation criteria weights and hesitant F-VIKOR is implemented to rank innovation project alternatives. A numerical example is given where five innovation projects are evaluated based on nine criteria by three decision makers.Article Citation - WoS: 2Citation - Scopus: 2Determination of Epidemic Parameters From Early Phase Fatality Data: a Case Study of the 2009 A(h1n1) Pandemic in Europe(World Scientific Publ Co Pte Ltd, 2018) Bilge, Ayşe Hümeyra; Samanlıoğlu, FundaThis paper demonstrates that the susceptible-infected-removed (SIR) model applied to the early phase of an epidemic can be used to determine epidemic parameters reliably. As a case study the SIR model is applied to the fatality data of the 2009 fall wave cycle of the A(H1N1) pandemic in 12 European countries. It is observed that the best estimates of the basic reproduction number R-0 and the mean duration of the infection period 1/eta lie on a curve in the scatterplots indicating the existence of a nearly-invariant quantity which corresponds to the duration of the epidemic. Spline interpolation applied to the early phase of the epidemic an approximately 10-week period together with a future control point in the stabilization region is sufficient to estimate model parameters. The SIR model is run over a wide range of parameters and estimates of R0 in the range 1.2-2.0 match the values in the literature. The duration of the infection period 1/eta is estimated to be in the range 2.0-7.0 days. Longer infection periods are tied to spatial characteristics of the spread of the epidemic.Article Citation - WoS: 22Citation - Scopus: 26Evaluation of Irrigation Methods in Soke Plain With Hf-Ahp Ii Hybrid Mcdm Method(Elsevier, 2022) Burak, Selmin; Samanlıoğlu, Funda; Ulker, DuyguSoke 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.Article Citation - WoS: 36Citation - Scopus: 47Evaluation of the Covid-19 Pandemic Intervention Strategies With Hesitant F-Ahp(Hindawi, 2020) Samanlıoğlu, Funda; Kaya, Burak ErkanIn this study, a hesitant fuzzy AHP method is presented to help decision makers (DMs), especially policymakers, governors, and physicians, evaluate the importance of intervention strategy alternatives applied by various countries for the COVID-19 pandemic. In this research, a hesitant fuzzy multicriteria decision making (MCDM) method, hesitant fuzzy Analytic Hierarchy Process (hesitant F-AHP), is implemented to make pairwise comparison of COVID-19 country-level intervention strategies applied by various countries and determine relative importance scores. An illustrative study is presented where fifteen intervention strategies applied by various countries in the world during the COVID-19 pandemic are evaluated by seven physicians (a professor of infectious diseases and clinical microbiology, an infectious disease physician, a clinical microbiology physician, two internal medicine physicians, an anesthesiology and reanimation physician, and a family physician) in Turkey who act as DMs in the process.Conference Object 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.Article Citation - WoS: 8Citation - Scopus: 13A Heuristic Approach for Allocation of Data To Rfid Tags: A Data Allocation Knapsack Problem (dakp)(Pergamon-Elsevier Science Ltd, 2012) Davis, Lauren; Samanlıoğlu, Funda; Jiang, Xiaochun; Mota, Daniel; Stanfield, PaulDurable products and their components are increasingly being equipped with one of several forms of automatic identification technology such as radio frequency identification (RFID). This technology enables data collection, storage, and transmission of product information throughout its life cycle. Ideally all available relevant information could be stored on RFID tags with new information being added to the tags as it becomes available. However, because of the finite memory capacity of RFID tags along with the magnitude of potential lifecycle data, users need to be more selective in data allocation. In this research, the data allocation problem is modeled as a variant of the nonlinear knapsack problem. The objective is to determine the number of items to place on the tag such that the value of the "unexplained" data left off the tag is minimized. A binary encoded genetic algorithm is proposed and an extensive computational study is performed to illustrate the effectiveness of this approach. Additionally, we discuss some properties of the optimal solution which can be effective in solving more difficult problem instances. (C) 2011 Elsevier Ltd. All rights reserved.Book Part A Network Model for the Location-Routing Decisions of a Logistics Company(Institute of Industrial Engineers, 2012) Sama, Funda; Yücekaya, Ahmet; Ayağ, ZekiIn 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%.
