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

Sustainable Development Goals Report Points

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Scholarly Output

51

Articles

38

Citation Count

819

Supervised Theses

4 Scholarly Output Search Results

Now showing 1 - 10 of 24

Citation - WoS: 2
Citation - Scopus: 2
Efficient Approaches for Furnace Loading of Cylindrical Parts
(Elsevier Science Inc, 2014) Osman, Mojahid Saeed; Samanlıoğlu, Funda; Ram, Bala; Samanlıoğlu, Funda; Industrial Engineering
This 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.
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; Industrial Engineering
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: 3
Citation - Scopus: 3
Solution approaches for the bi-objective Skiving Stock Problem
(Pergamon-Elsevier Science Ltd, 2023) Samanlıoğlu, Funda; Samanlıoğlu, Funda; Altay, Ayca; Industrial Engineering
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 - WoS: 19
Citation - Scopus: 24
Evaluation of Irrigation Methods in Soke Plain With Hf-Ahp Ii Hybrid Mcdm Method
(Elsevier, 2022) Burak, Selmin; Samanlıoğlu, Funda; Samanlıoğlu, Funda; Ulker, Duygu; Industrial Engineering
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.
Citation - WoS: 41
Citation - Scopus: 43
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.; Industrial Engineering
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: 11
Citation - Scopus: 13
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; Industrial Engineering
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.
A Fuzzy Best-Worst Multi-Criteria Decision-Making Method for Third-Party Logistics Provider Selection
(Kadir Has Üniversitesi, 2016) Boakai, Sylivan; Samanlıoğlu, Funda; Samanlıoğlu, Funda; Industrial Engineering
In recent years, the outsourcing of logistics functions to a third-party has been a major alternative to vertical integration. Third-party logistics provider can serve as a significant source of competitive advantage for firms aiming to focus on their core competencies. In selecting a strategic third-party logistics partner, there are many criteria and potential providers that must be carefully evaluated. Hence, third-party logistics provider selection is a multi-criteria decision-making problem; and it is extremely important that decision makers have a reliable decision support tool to select the best partner. Several multi-criteria decision making methods have been proposed. Some of these methods like Analytical Hierarchy Process (AHP) and Analytic Network Process (ANP) require decision-makers to use pairwise comparisons in order to determine their preferences. However, due to the large number of criteria and potential providers associated with third-party logistics selection decision, these pairwise comparisons might lead to a reduction in the overall consistency. This thesis addresses this issue by extending the newly proposed best-worst method to incorporate decision-makers' uncertainty and vagueness while requiring fewer comparisons as compared to a method like Fuzzy AHP. The aim of this thesis is twofold: first, a fuzzy best-worst multi-criteria decision-making method is proposed to handle the issue of larger number of comparisons and uncertainty in judgements. Secondly, the proposed method is applied to a third-party logistics selection problem at a medium-sized company in Turkey. The results of the study show that the proposed method efficiently handles decision maker's inherent uncertainty while requiring fewer number of comparisons.
Citation - WoS: 6
Citation - Scopus: 7
An Interactive Memetic Algorithm for Production and Manufacturing Problems Modelled as a Multi-Objective Travelling Salesman Problem
(Taylor & Francis Ltd, 2012) Samanlıoğlu, Funda; Samanlıoğlu, Funda; Ferrell, William G.; Kurz, M. E.; Industrial Engineering
In this paper a preference-based interactive memetic random-key genetic algorithm (PIMRKGA) is developed and used to find (weakly) Pareto optimal solutions to manufacturing and production problems that can be modelled as a symmetric multi-objective travelling salesman problem. Since there are a large number of solutions to these kinds of problems to reduce the computational effort and to provide more desirable and meaningful solutions to the decision maker this research focuses on using interactive input from the user to explore the most desirable parts of the efficient frontier instead of trying to reproduce the entire frontier. Here users define their preferences by selecting among five classes of objective functions and by specifying weighting coefficients bounds and optional upper bounds on indifference tradeoffs. This structure is married with the memetic algorithm - a random-key genetic algorithm hybridised by local search. The resulting methodology is an iterative process that continues until the decision maker is satisfied with the solution. The paper concludes with case studies utilising different scenarios to illustrate possible manufacturing and production related implementations of the methodology.
Analysis of the Stochastic Skiving Stock Problem
(Kadir Has Üniversitesi, 2022-04) KARACA, TOLGA KUDRET; Samanlıoğlu, Funda; Samanlıoğlu, Funda; Industrial Engineering
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: 2
Citation - Scopus: 1
Evaluation of Gas-Fired Combi Boilers with HF-AHP-MULTIMOORA
(Hindawi Ltd, 2022) Samanlıoğlu, Funda; Ayağ, Zeki; Kirkil, Goekhan; Yucal, Esra; Industrial Engineering
There are many alternative gas-fired combi boilers that can be used to heat residential homes. Evaluation and selection of gas-fired combi boilers for buildings is an intricate multi-criteria decision-making (MCDM) problem involving perhaps contradictory quantifiable and qualitative criteria. In this research, as the MCDM approach, hesitant fuzzy linguistic analytic hierarchy process (HF-AHP) and hesitant fuzzy linguistic multiple objective optimization based on ratio analysis plus full multiplicative form (MULTIMOORA) (HF-MULTIMOORA) are integrated to assess and rank combi boiler alternatives for buildings. First, with HF-AHP, fuzzy criteria weights are determined and then with HF-MULTIMOORA, boiler alternatives are ranked from best to worst. In this integrated HF-AHP-MULTIMOORA method, evaluations of decision-makers are combined with fuzzy envelope approach and then triangular fuzzy numbers are utilized. For comparison analysis, HF-AHP-TOPSIS method is also applied to the same problem. A case study in Turkey is presented where ten combi boiler alternatives are assessed based on fifteen criteria by five decision-makers. We have used various selection criteria for boilers ranging from maximum temperature, heating capacity up to environmental effects and decided on the best combi boiler for heating residential buildings in Turkey.