Academic Positions

  • Present

    Assistant Professor Dr.

    Suleyman Demirel University,
    Dept. of Industrial Engineering

  • Feb 2016 Jul 2015

    Visiting Researcher

    Helmut Schmidt University,
    Dept. of Logistics Management

  • Present Jul 2013

    Assistant Professor Dr.

    Suleyman Demirel University,
    Dept. of Industrial Engineering

  • Jul 2013 Mar 2013

    Research Assistant Dr.

    Suleyman Demirel University,
    Dept. of Industrial Engineering

  • Mar 2013 Dec 2006

    Research Assistant

    Suleyman Demirel University,
    Dept. of Industrial Engineering

Education

  • PhD. March 2013

    Mechanical Engineering

    Suleyman Demirel University
    Graduate Sch. of Natural and Applied Sciences

  • MSc. January 2009

    Industrial Engineering

    Suleyman Demirel University
    Graduate Sch. of Natural and Applied Sciences

  • BSc. July 2005

    Industrial Engineering

    Selcuk University
    Engineering and Architecture Faculty

Research Projects

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    Alternative Solution Approaches to Vehicle Routing Problems

    Researcher, Pamukkale University BAP 2013-BSP-0026, 2013-2016.

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    Android Based Inventory Management System

    Academic Supervisor, TUBITAK 2209/A Bachelor Students Research Projects, 2014-2015.

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    Research and Analysis on a Furniture Production System via Value Stream Mapping and Work Study

    Academic Supervisor, TUBITAK 2209/A Bachelor Students Research Projects, 2013-2014.

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    Development of an EPQ Model with Imperfect Items using Grey System Theory

    Researcher, Suleyman Demirel University BAP 2918-D-11, 2011-2013.

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    Development of Simulation Software for Facility Organizing, Production System Structuring, and Performance Measuring (Faborg-Sim)

    Researcher, TUBITAK MAG 1001 Research Projects 104-M-377, 2006-2009.

SCI, SCI-Expanded and SSCI Papers [11 papers]

A New Approach for Interval Grey Numbers: n-th Order Degree of Greyness

Aydemir E.
SCI-E The Journal of Grey Systems, 32(x), Article in Press, 2020.

Abstract

Uncertain information has complexity for various reasons in real-life decision-making problems in order to be useful information. Therefore, it is deeply interesting to study the characterization and size measurement of uncertain information. Therefore, the purpose of this paper is to investigate the n-th order level of degree of greyness for analyzing as a new approach on distance measuring and sorting methods for general grey numbers. Also, a pseudocode form is given for the proposed method and illustrated by using an interval number and its effects are presented on some experimental solutions.

A bi-objective inventory routing problem with interval grey demand data

Kahraman O.U., Aydemir E.
SCI-E Grey Systems: Theory and Application, Vol. 10 No. 2, pp. 193-214, 2020.

Abstract

Purpose The purpose of this paper is to manage the demand uncertainty considered as lower and upper levels for a medium-scale industrial distribution planning problem in a biobjective inventory routing problem (IRP). In order to achieve this, the grey system theory is applied since no statistical distribution from the past data and incomplete information. Design/methodology/approach This study is investigated with optimizing the distribution plan, which involves 30 customers of 12 periods in a manufacturing company under demand uncertainty that is considered as lower and upper levels for a biobjective IRP with using grey demand parameters as a grey integer programming model. In the data set, there are also some missing demand values for the customers. So, the seven different grey models are developed to eliminat the effects on demand uncertainties in computational analysis using a piece of developed software considering the logistical performance indicators such as total deliveries, total cost, the total number of tours, distribution capacity, average remaining capacity and solution time. Findings Results show that comparing the grey models, the cost per unit and the maximum number of vehicle parameters are also calculated as the new key performance indicator, and then results were ranked and evaluated in detail. Another important finding is the demand uncertainties can be managed with a new approach via logistics performance indicators using alternative solutions. Practical implications The results enable logistics managers to understand the importance of demand uncertainties if more reliable decisions are wanted to make with obtaining a proper distribution plan for effective use of their expectations about the success factors in logistics management. Originality/value The study is the first in terms of the application of grey models in a biobjective IRP with using interval grey demand data. Successful implementation of the grey approaches allows obtaining a more reliable distribution plan. In addition, this paper also offers a new key performance indicator for the final decision.

A Grey Production Planning Model on a Ready-Mixed Concrete Plant

Aydemir E., Yılmaz G., Oruc K.O.
SCI-E Engineering Optimization, 52 (5), pp. 817-831, 2020.

Abstract

The parameters of decision models are not clearly known and they are not exact for most real-life problems. Therefore, this article presents a model of linear programming with grey interval numbers for right-hand-side parameters under an uncertainty case. The purpose of this article is to compare the results of a fuzzy linear programming model and those of four proposed grey linear programming models and to find effective solutions for alternative production planning. The results produced a more effective plan to use as an industrial solution according to a fuzzy linear programming model. The objective function value is about 3% more effective than with the fuzzy linear programming method, and the customer satisfaction of total demand is about 25% more effective for the number of served customers.

Evaluation of Healthcare Service Quality Factors Using Grey Relational Analysis in a Dialysis Center

Aydemir E., Sahin Y.
SCI-E Grey Systems: Theory and Application, 9(4), pp. 432-448, 2019.

Abstract

Purpose The purpose of this paper is to investigate the relative influences of technical and functional quality levels of service quality and patient satisfaction. In this context, the healthcare service quality and the factors affecting customer satisfaction were evaluated using the grey relational analysis (GRA) method. Design/methodology/approach This is a survey-based study which involves 15 patients in a dialysis center, so the GRA is applied to clarify the uncertainty on service quality level with a limited number of patients without any statistical distribution. In order to reveal whether service quality and customer satisfaction are two different structures, a GRA model is built with ten different quality factors. Findings Results show that each quality factor has a different effect on the quality of service. Another important finding is that service quality and customer satisfaction are different structures for customers. Practical implications The results enable healthcare managers to understand the importance of patient care and the importance of service quality if they want to facilitate their use of their expectations in related factors. Originality/value The study is the first in terms of the application of GRA models in a private health institution operating in Turkey. Successful implementation of the GRA method allows a reasonable decision to be made with a limited number of data at hand. It is considered that the method can be used successfully in other health institutions in the Turkish Health System.

Breeder Hybrid Algorithm Approach for Natural Gas Demand Forecasting Model

Karadede y., Ozdemir G., Aydemir E.
SCIEnergy, 141C, pp. 1269-1284, 2017.

Abstract

A breeder hybrid algorithm consisting of the constitution of nonlinear regression-based breeder genetic algorithm and simulated annealing is proposed for the objective of forecasting the natural gas demand with a smaller error rate. The main aim of this study is to show general natural gas demand forecasting model of the breeder hybrid algorithm based nonlinear regression. The most important difference that distinguishes this natural gas demand forecasting model from other models in the literature is that the proposed model evolves continuously with the best solutions in both the breeder genetic algorithm and simulated annealing parts. It is applied to Turkey natural gas demand forecasting to show its superiority and applicability. The consumption amount of natural gas has between 1985 and 2000 is determined as dependent variable whereas the independent variables are determined as the gross national product, population and the growth rate. Then, the consumption amounts of natural gas between 2001 and 2014 are forecasted with significantly small MAPE values that are obtained 0.0188 and 0.0143 for year 2014 using the proposed algorithms and compared to different solutions in the literature. The proposed algorithms are superior to the comparable algorithms in the literature. Then, two scenarios are applied for the years between 2015 and 2030 for future projection.

Forecasting of Turkey Natural Gas Demand Using a Hybrid Algorithm

Ozdemir G., Aydemir E., Olgun M.O., Mulbay Z.,
SCI-E Energy Sources Part B- Economics Planning and Policy, 11 (4), pp. 295-302, 2016.

Abstract

The basis of the energy management constitutes the forecasting of the need for energy as much as accurate. In this study, a hybrid genetic algorithm-simulated annealing (GA-SA) algorithm based on linear regression has been developed and coded as software to forecast natural gas demand of Turkey. The linear models, which are constructed by using the amounts of natural gas consumption for years between 1985 and 2000 as dependent variable, and gross national product, population, and growth rate as independent variables, are used to forecast the amount of natural gas consumption for years between 2001 and 2009. Then, the forecasts are compared with real amounts of consumptions and are analyzed statistically. Consequentially, it is observed that the GA-SA hybrid algorithm made forecasts with less statistical error against linear regression. The models were used to forecast Turkey’s natural gas demand under two different scenarios for years between 2010 and 2030.

A New Production Scheduling Module Using Priority-Rule Based Genetic Algorithm

Aydemir E., Koruca H.İ.
SCI-E International Journal of Simulation Modelling, 14 (3), pp. 450-462, 2015

Abstract

Production scheduling is an important function that determines the efficiency and productivity of a production system. Many optimization methods, techniques, tools, and heuristics have been used to solve production scheduling problems, accordingly priority rules are implemented for customers’ orders in real-world applications. Simulations and heuristic methods are quite useful for making decisions, and they are used mostly to design and improve production systems by reducing their complexity. In this study, a Priority Rule-Based Genetic Algorithm Scheduling (PRGA-Sched) module was developed to provide shorter total completion time in production scheduling. The module was integrated with the Faborg-Sim simulation tool. As a case study, a heating boiler manufacturing system was analyzed and simulated with six products and customers’ orders by using production data from the PRGA-Sched module in Faborg-Sim. The results showed that a shorter total completion time is obtained and saved than the initial situation by via PRGA-Sched module.

Degree of greyness approach for an EPQ model with imperfect items in a copper wire industry

Aydemir E., Bedir F., Ozdemir G.
SCI-E Journal of Grey System, 27 (2), pp. 13-26, 2015.

Abstract

Economic production quantity (EPQ) models must have been developed to determine the optimal production quantity which included the different uncertainty of the manufacturing systems even though they were to be deterministic, such as variations of demand and related cost values etc. Also we know that the basic assumption of EPQ model is that 100% of manufactured products are non-defective and no shortages. In this paper, we aimed to develop an EPQ model which has been extended with grey demand rate, grey cost values and allowed maximum backorder level under imperfect items in a copper wires manufacturing system by using degree of greyness approach. Here, the imperfect items have been defined as three levels: good quality, low quality and scrap items. The degree of greyness value has been placed to whitenization coefficient for each parameter and the whole system separately. The mathematical model has been developed and the results are considered with the behaviors of the system under the uncertainty with a practical case studies of a copper wire production system.

Forecasting of Turkey’s Natural Gas Demand Using Artifical Neural Networks and Support Vector Machines

Olgun M.O., Ozdemir G., Aydemir E.
SCI-E Energy Education Science and Technology Part A: Energy Science and Research, 30 (1), pp. 15-20, 2012.

Abstract

The basis for energy management is to estimate the demand for energy as accurately as possible and without error. There are many studies related to demand forecasting in the literature. In this study, the support vector machines and artificial neural networks models were used to estimate the natural gas demand of Turkey. The correct forecasting of natural gas consumption plays an important role for the amount of natural gas production, and to reveal import and export policies. A natural gas consumption model is developed by using the data from years between 1985 and 2000 where gross national product and population are independent variables in Turkey. This model is used to estimate the natural demand for years 2001 and 2006 and results are compared with real consumptions. Then, statistical analyses are conducted and the results are compared with studies in the literature. In conclusion, it is observed that support vector machines have less statistical error comparing to artificial neural networks for demand estimation of natural gas consumption in Turkey. The models which are obtained by using support vector machines are run for four different scenarios and the natural gas demand forecasts are obtained for Turkey until year of 2030.

The Simulation-Based Performance Measurement in An Evaluation Module for Faborg-Sim Simulation Software

Koruca H.I., Ozdemir G., Aydemir E., Cayirli M.
Journal Paper SCI-E Expert System with Applications, 37 (12), pp. 8211-8220, 2010.

Abstract

It is possible to evaluate production system performance measurement and organizational alternative structures with dynamic simulation methods for efficiency of cost and productivity. The parameters which are vary for different organizational structures and scope of production systems are examined in a mutual simulation-based performance measurement system. In general, the simulation-based performance measurement criteria are lead time, lead time deviation, utilization rate, and work-in-process as goal achievements of logistics and delivery rate in performance evaluation module.In this study, an evaluation module is developed and integrated to system simulation results as a part of the research project of ‘‘Development of Simulation Software for Facility Organizing, Production System Structuring, and Performance Measuring (Faborg-Sim)” at Suleyman Demirel University Industrial Engineering Department which is supported by The Scientific and Technological Research Council of Turkey(TUBITAK).

Development Of Flexible Work Flow Plan Editor In Faborg-Sim And Operations Scheduling On Gantt Charts

Koruca H.I., Ozdemir G., Aydemir E., Cayirli M.
SCI-E Journal of Fac. Eng. Arch. Gazi University, 25(1), pp. 77-81, 2010.

Abstract

System information can be transferred into computer environment with more accuracy than ever before and simulation can be used efficiently with the development of object oriented programming. It is important integration of system data into the software by using work flow plan drawings with scheduling of simulation results on a Gantt diagram when searching alternative structure and flow organizations in simulation of production systems. In this study, a flexible work flow editor is developed to model system data and work processes and to draw real time Gantt diagrams as a part of the research project of “Development of Simulation Software for Facility Organizing, Production System Structuring, and Performance Measuring (Faborg-Sim)” which is supported by TUBITAK-MAG.

Journal Papers [20 papers]

A New Approach for Interval Grey Numbers: n-th Order Degree of Greyness

Aydemir E.
SCI-E The Journal of Grey Systems, 32(x), Article in Press, 2020.

Abstract

Uncertain information has complexity for various reasons in real-life decision-making problems in order to be useful information. Therefore, it is deeply interesting to study the characterization and size measurement of uncertain information. Therefore, the purpose of this paper is to investigate the n-th order level of degree of greyness for analyzing as a new approach on distance measuring and sorting methods for general grey numbers. Also, a pseudocode form is given for the proposed method and illustrated by using an interval number and its effects are presented on some experimental solutions.

Undergraduate

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    ENM-101 Introduction to Industrial Engineering

    Weeks
    Subjects
    1
    Overview of Industrial Engineering
    2
    Information Management, Competition, Strategy and Productivity
    3
    Fundamentals of Statistics an Forecasting Methods
    4
    Production Systems and Facility Planning
    5
    Work Study
    6
    Quality Engineering and Total Quality Management
    7
    Process Management
    8
    Fundamentals of Operational Research
    9
    Manufacturing Resources Planning
    10
    Production Planning
    11
    Scheduling
    12
    Inventory and Supply Chain Management
    13
    Simulation
    14
    Intelligence Manufacturing Systems

    Materials
    - Lecture Notes
    - Book: (Turkish) Oztemel, E. (Editor), Introduction to Industrial Engineering, Papatya Publishing, 2012.
    - Book: (English) Zandin, K., Maynard's Industrial Engineering Handbook , Mc-Graw Hill, 2001.
    - Industrial Case Studies from Scientific Literature
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    ENM-205 Database Management

    Weeks
    Subjects
    1
    Data
    2
    Introduction to Database Management Systems
    3
    Entity-Relation Models I
    4
    Entity-Relation Models II
    5
    Normailization I
    6
    Normailization II
    7
    MS Access Design I
    8
    MS Access Design II
    9
    MS Access Design III
    10
    SQL I
    11
    SQL II
    12
    SQL III
    13
    Using LINQ
    14
    Project Presentations

    Materials
    - Lecture Notes
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    END-331 Project Management

    Weeks
    Subjects
    1
    Introduction to Project Management
    2
    Gantt Diagrams and Work Breakdowns Structures
    3
    Critical Path Method (CPM)
    4
    Program Evaluation and Review Technique (PERT)
    5
    Resource Management
    6
    Budget and Cost Management I
    7
    Budget and Cost Management II
    8
    Software Applications I
    9
    Software Applications II
    10
    Software Applications III
    11
    Software Applications IV
    12
    Project Presentations I
    13
    Project Presentations II
    14
    Project Presentations III

    Materials
    - Lecture Notes
    - Book: (Turkish) Dirlik, Y., MS Project 2013, Kodlab Publishing, 2014.
    - Book: (English) PMI, A Guide to the Project Management Body of Knowledge: PMBOK(R) Guide, 2013.
    - Papers from Scientific Literature
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    END-356 Inventory Theory

    Weeks
    Subjects
    1
    Introduction to Inventory Management
    2
    Demand Forecasting I
    3
    Demand Forecasting II
    4
    Demand Forecasting III
    5
    Inventory Control
    6
    Deterministic Inventory Models I
    7
    Deterministic Inventory Models II
    8
    Deterministic Inventory Models III
    9
    Stochastic Inventory Models I
    10
    Stochastic Inventory Models II
    11
    Master Production Scheduling
    12
    Lot Sizing I
    13
    Lot Sizing II
    14
    Lot Sizing III

    Materials
    - Lecture Notes
    - Book: (Turkish) Yenersoy, G., Production Planning, Papatya Publishing, 2012.
    - Book: (English) Nahmias, S., Production and Operations Analysis, Mc-Graw Hill, 2006.
    - Papers from Scientific Literature
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    END-437 Decision Analysis

    Weeks
    Subjects
    1
    Introduction to Decision Theory
    2
    Decision Making Process and Decision Trees
    3
    Decision Making Under Risk I
    4
    Decision Making Under Risk II
    5
    Decision Making under Uncertainty I
    6
    Decision Making under Uncertainty II
    7
    Group Decision Making
    8
    Multi Criteria Decision Making (MCDM)
    9
    MCDM - ANP
    10
    MCDM - AHP
    11
    MCDM - ELECTRE
    12
    MCDM - TOPSIS
    13
    MCDM - PROMETHE
    14
    Fundamentals of Game Theory

    Materials
    - Lecture Notes
    - Book: (Turkish) Yildirim B.F. (Editor), Multi Criteria Decision Making Methods, Dora Publishing, 2014.
    - Papers from Scientific Literature

Graduate

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    01END5121 Inventory Systems Management

    Weeks
    Subjects
    1
    Introduction to Inventory Management
    2
    Demand Forecasting I
    3
    Demand Forecasting II
    4
    Demand Forecasting III
    5
    Inventory Control
    6
    Deterministic Inventory Models I
    7
    Deterministic Inventory Models II
    8
    Deterministic Inventory Models III
    9
    Stochastic Inventory Models I
    10
    Stochastic Inventory Models II
    11
    Master Production Scheduling
    12
    Lot Sizing I
    13
    Lot Sizing II
    14
    Lot Sizing III

    Materials
    - Lecture Notes
    - Book: (Turkish) Yenersoy, G., Production Planning, Papatya Publishing, 2012.
    - Book: (English) Nahmias, S., Production and Operations Analysis, Mc-Graw Hill, 2006.
    - Papers from Scientific Literature
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    01END5131 Grey Systems Theory

    Weeks
    Subjects
    1
    Introduction to Grey Systems Theory
    2
    Grey Number and Operations
    3
    Grey Equations
    4
    Grey Sequences
    5
    Grey Incidence Analysis
    6
    Grey Clustering and Statistical Analysis
    7
    Grey System Modelling
    8
    Grey Combined Models
    9
    Grey Prediction Models
    10
    Grey Decision Making Models
    11
    Grey Linear-Nonlinear Programming
    12
    Grey Game Theory
    13
    Grey Input-Output Analysis
    14
    Grey Control Systems

    Materials
    - Lecture Notes
    sss
    - Book: (English) Liu S., Lin Y., Grey Information: Theory and Practical Applications. SpringerVerlag, 2006.
    - Book: (English) Liu S., Lin Y., Grey Systems with Applications. SpringerVerlag, 2010.
    - Industrial Case Studies from Scientific Literature
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    01END5134 Intelligent Forecasting Models

    Weeks
    Subjects
    1
    Introduction to Forecasting
    2
    Statistical Preliminaires
    3
    Causal Methods I
    4
    Causal Methods II
    5
    Time Series Models I
    6
    Time Series models II
    7
    Error Analysis
    8
    Intelligent Forecasting Models: Artifical Neural Networks
    9
    Intelligent Forecasting Models: Fuzzy Logic
    10
    Intelligent Forecasting Models: Grey System Theory
    11
    Intelligent Forecasting Models: Metaheuristics/Matheuristics
    12
    Project Presentations I
    13
    Project Presentations II
    14
    Project Presentations III

    Materials
    - Lecture Notes
    - Book: (English) Makridakis S., et al. Forecasting: Methods and Applications, Wiley, 1998.
    - Papers from Scientific Literature
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    01END6116 Multi Criteria Decision Making

    Weeks
    Subjects
    1
    Introduction to Decision Theory
    2
    Decision Making Process and Decision Trees
    3
    Decision Making Under Risk
    4
    Decision Making under Uncertainty
    5
    Utility Theory and Group Decision Making
    6
    Introduction to Multi Criteria Decision Making (MCDM)
    7
    MCDM - ANP
    8
    MCDM - AHP
    9
    MCDM - ELECTRE
    10
    MCDM - TOPSIS
    11
    MCDM - PROMETHE
    12
    MCDM - GRA
    13
    Fundamentals of Game Theory
    14
    Markov Process

    Materials
    - Lecture Notes
    - Book: (Turkish) Yildirim B.F. (Editor), Multi Criteria Decision Making Methods, Dora Publishing, 2014.
    - Papers from Scientific Literature

At My Office

You can find me at my office (E13-104)located at Engineering Faculty of Suleyman Demirel University, Isparta, TURKIYE

Please you can contact by an e-mail at my first choice