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

ORCID ID

0000-0003-3838-8824

Scopus Author ID

23012602800

Full item page

Scholarly Output

43

Articles

31

Citation Count

819

Supervised Theses

4 Scholarly Output Search Results

Now showing 1 - 10 of 43

Analysis of the stochastic skiving stock problem
(Kadir Has Üniversitesi, 2022-04) 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 Count: 2
An MCDM approach to third party logistics provider selection
(Inderscience Publishers, 2023) Samanlıoğlu, Funda; Samanlıoğlu, Funda
In order to focus on their main skills and be more competitive and efficient in business, firms frequently outsource their logistics functions to a third party logistics (3PL) provider. Evaluation and selection of a 3PL provider is a multi-criteria decision-making (MCDM) process due to the need to take into consideration various potentially competing qualitative and quantitative criteria. In this paper, as the MCDM method, fuzzy best-worst method (BWM) is applied to a 3PL provider selection problem of a textile company in Turkey. Here, six 3PL provider alternatives are evaluated with respect to 15 criteria by three managers (decision makers). Fuzzy BWM incorporates decision makers’ imprecision and ambiguity to the decision-making process and requires fewer pairwise comparisons than a frequently used method in 3PL provider selection, fuzzy analytic hierarchy process (AHP). Consistent results are always obtained through using fuzzy BWM, though not fully consistent. Copyright © 2023 Inderscience Enterprises Ltd.
Citation Count: 39
Computing trade-offs in robust design: Perspectives of the mean squared error
(Pergamon-Elsevier Science Ltd, 2011) 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 Count: 17
Concept selection with hesitant fuzzy ANP-PROMETHEE II
(Taylor & Francis Ltd, 2021) Samanlıoğlu, Funda; Ayag, Zeki
An integrated approach is given for the assessment and ranking of concepts as part of the new product development (NPD) process. Selection of the best concept in NPD involves multiple criteria decision-making (MCDM) since there are numerous possibly competing criteria to consider. Here, hesitant fuzzy Analytic Network Process (H-F-ANP) and hesitant fuzzy Preference Ranking Organization Method for Enriching Evaluations II (H-F-PROMETHEE II) are integrated to assess the concepts and determine the best. In the hesitant fuzzy ANP-PROMETHEE II (H-F-ANP-PROMETHEE II), H-F-ANP is applied to calculate criteria weights, taking into consideration inner and outer dependence and feedback interactions between criteria and H-F-PROMETHEE II is implemented to rank concept alternatives, employing the calculated criteria weights. A demonstrative example is given where five concepts are evaluated by three decision makers (DMs) to exhibit the applicability. For comparison, H-F-ANP-VIKOR is utilized.
Citation Count: 47
A fuzzy AHP-PROMETHEE II approach for evaluation of solar power plant location alternatives in Turkey
(IOS Press, 2017) Samanlıoğlu, Funda; Ayağ, Zeki
Solar energy produced through a solar power plant is a freely available non-polluting renewable source of energy that reduces the greenhouse effect. Selecting the best location for a solar power plant among several location alternatives is a complicated multiple criteria decision making (MCDM) problem since several potentially conflicting quantitative and qualitative criteria needs to be taken into consideration. In this paper of the most commonly used MCDM methods in literature
Citation Count: 135
Inventory planning and coordination in disaster relief efforts
(Elsevier Science Bv, 2013) Samanlıoğlu, Funda; Samanlıoğlu, Funda; Qu, Xiuli; Root, Sarah
This research proposes a stochastic programming model to determine how supplies should be positioned and distributed among a network of cooperative warehouses. The model incorporates constraints that enforce equity in service while also considering traffic congestion resulting from possible evacuation behavior and time constraints for providing effective response. We make use of short-term information (e.g. hurricane forecasts) to more effectively preposition supplies in preparation for their distribution at an operational level. Through an extensive computational study we characterize the conditions under which prepositioning is beneficial as well as discuss the relationship between inventory placement capacity and coordination within the network. (C) 2012 Elsevier B.V. All rights reserved.
A fuzzy best-worst multi-criteria decision-making method for third-party logistics provider selection
(Kadir Has Üniversitesi, 2016) Samanlıoğlu, Funda; Samanlıoğlu, Funda
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 Count: 0
A Two-Phase Pattern Generation and Production Planning Procedure for the Stochastic Skiving Process
(Hindawi Ltd, 2023) Samanlıoğlu, Funda; Samanlioglu, Funda; Altay, Ayca
The stochastic skiving stock problem (SSP), a relatively new combinatorial optimization problem, is considered in this paper. The conventional SSP seeks to determine the optimum structure that skives small pieces of different sizes side by side to form as many large items (products) as possible that meet a desired width. This study studies a multiproduct case for the SSP under uncertain demand and waste rate, including products of different widths. This stochastic version of the SSP considers a random demand for each product and a random waste rate during production. A two-stage stochastic programming approach with a recourse action is implemented to study this stochastic NP-hard problem on a large scale. Furthermore, the problem is solved in two phases. In the first phase, the dragonfly algorithm constructs minimal patterns that serve as an input for the next phase. The second phase performs sample-average approximation, solving the stochastic production problem. Results indicate that the two-phase heuristic approach is highly efficient regarding computational run time and provides robust solutions with an optimality gap of 0.3% for the worst-case scenario. In addition, we also compare the performance of the dragonfly algorithm (DA) to the particle swarm optimization (PSO) for pattern generation. Benchmarks indicate that the DA produces more robust minimal pattern sets as the tightness of the problem increases.
Citation Count: 0
Routing decisions in an earthquake relief network
(Institute of Industrial Engineers, 2014) Samanlıoğlu, Funda; Uğur, Mehmet Fatih; Güç, Mehmet Akif; Gün, Hüseyin Safa; Samanlıoğlu, Funda; Yurduseven, Uğurcan
In this paper, a mathematical model is developed in order to configure part of the earthquake relief network in Istanbul, Turkey. The aim of the mathematical model is to help decision makers decide on the routing of different types of relief aids (food, drug, and tent) from the local airport to the main distribution centers; from the main distribution centers to sub-distribution centers and from these centers to the tent areas and meeting points of people in need, while minimizing the total cost of transportation and taking into consideration capacity restrictions, and demand of end points. The mathematical model is implemented in a pilot area in Istanbul, Atasehir municipality, and solved optimally with LINGO 7.0 solver. The related data is obtained from Atasehir municipality, Search & Rescue Association (AKUT), and Disaster Coordination Center (AKOM).
Citation Count: 7
On the uniqueness of epidemic models fitting a normalized curve of removed individuals
(Springer Heidelberg, 2015) Bilge, Ayşe Hümeyra; Samanlıoğlu, Funda; Ergönül, Önder
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, , 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 and , where is the steady state value of and and are the values of and its derivative at the inflection point of . 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.