Yüksek Lisans Tezleri

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/7775

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An Analysis of Development Indicators for Turkey Based on the Historical Development of 500 Largest Industrial Organizations
(Kadir Has Üniversitesi, 2015) Otnar, Ferhan; Yücekaya, Ahmet Deniz
Economies live rapid changes in terms of size direction and intention due to globalization population increase of countries and technological developments. These changes seemed clearer in developing countries because of fast progress and demand increases. Especially in last 10 year period Turkey gained economical acceleration along with growth and development. Parallel to these developments diversification in industrial areas and evolvement in remained areas used as an answer. in this aspect istanbul Chamber of industry announced Turkey's top 500 industrial enterprises each year. in this study Turkey's developing economy was analyzed with iSO Top 500 List for 2002-2012 periods in order to identify vector sectors and economical variance. According to analysis changes in industrial effects on Turkey's economy were investigated.
A Behavioral Study for Examining the Compliance of Pricing Models in Revenue Management Theory With the Decisions of Human Decision Makers
(Kadir Has Üniversitesi, 2020) Erkol, Cüneyt; Çavdaroğlu, Nur; Ağca Aktunç, Esra; Çavdaroğlu, Nur; Aktunç, Esra Ağca
This study involves four computer-based experiments based on different assumptions which are performed in a laboratory-setting. The behavior patterns of the subjects and the degree of deviation of these behaviors from optimal strategies are analyzed by various statistical methods. The common aim of the experiments examined in this thesis is to understand how successful Revenue Management theoretical models are in explaining real human behavior. In various cases, it has been possible to determine in which direction deviations from theoretical models occur and causes can be understood. In static competitor price treatment (in experiments 1 and 2), subjects exhibit a higher tendency to underprice. The "gambler's fallacy" bias is the dominant behavioral pattern observed in dynamic price setting. Humans consistently make pricing decisions below theoretical optimum, and only a small minority of the subjects are able to make optimum pricing decisions, supporting the presence of bounded rationality. Higher cognitive reflection skills help perform decisions closer to optimal, although not significantly better. Maximizing tendency does not show significance in meeting neither the optimum price, nor the potential revenue. Higher risk appetite makes better decisions in a dynamic competitor price setting. Neither the impact of learning effect, nor the demand-chasing bias is prevalent in the findings. Anchoring on the competitor price is observable in dynamic price setting. The study is useful in revealing the human factor issues that companies aiming to increase their profitability should pay attention to. Furthermore, the study can also be helpful in determining information to be provided to decision makers by an effective decision support system, and it proposes recommendations regarding the measures companies can take to improve human decision makers' decisions.
Co-Optimization Models of Generation and Transmission Investments With Market-Clearing Equilibrium
(Kadir Has Üniversitesi, 2018) Uyan, Zeki; Çelebi, Emre
Methods for co-optimizing transmission and generation investments including bi-level or multi-level problems consider trade-offs with market operations and interactions in electric power supply and demand. Under fairly general conditions it is known that simultaneous solution of these multi-level models using complementarity problems can give more useful results than iterative optimization methods or single-level optimization of generation or transmission expansion alone. Hence in this thesis we provide mixed complementarity problem formulations for transmission and generation expansion models with electricity market-clearing models. in this study we have considered co-optimization models formulated as bi-level programming problems as well as single-level mixed complementarity problems. in the upper level of the bi-level problem the system operator decides on the transmission expansion plans while anticipating the decisions in the lower level of the problem. The lower level problems present models of generation expansion and oligopolistic competition among power generators in the market where we examine perfect competition models to Cournot game among generators. This model is essentially an economic equilibrium problem for electricity markets that is defined by the optimality conditions that examine system operator’s and generators’ expansion behavior along with supply-demand balance in the market. These models will be handful for planning generation/transmission expansions and analyzing the relations between these expansions and the market outcomes. We have simulated market outcomes and expansion decisions in a 6-bus test system and a realistic Turkish electricity market under two different market structures (perfect competition and Nash-Cournot). Furthermore four different scenarios considering carbon costs and feed-in-tariffs (FiT) for Turkish electricity market for December 2020 are simulated and results are examined. Scenario considering both carbon costs and FiT have provided relatively better results in terms of social welfare.
Decarbonization Pathways For Turkish Power System Using The Leap Model Leap Modeli Kullanılarak Türkiye Elektrik Sistemi için Dekarbonizasyon Yolları
(Kadir Has Üniversitesi, 2021) Özer, Fatma Ece; Kirkil, Gökhan; Yücekaya, Ahmet Deniz
The negative impact of GHG released into the atmosphere on global warming cannot be ignored. Fossil-fueled power plants constitute a large part of Turkey's electricity production, as every country has a growing economy. Therefore, the electricity generation sector accounts for a significant portion of GHG emissions in Turkey. In addition to national bindings such as the Paris Agreement and the Kyoto Protocol, it is known that the Republic of Turkey aims to make not only electricity but also energy production greener in the coming years, in line with its own efforts. For this purpose, there are different modeling studies in the literature. This thesis aims to model Turkey's electricity generation sector in 2017, reveal the current situation, and then analyze how a greener and sustainable energy transformation will be possible with different scenarios and different main factors. In this direction, Turkey's electricity generation sector was modeled using the LEAP tool, then the decarbonization scenarios created within the openENTRANCE project were adapted to Turkey's data, and the numerical results of the scenarios were compared. As a result, it has been revealed that social awareness, adaptation to new technologies, and incentives of decision-makers are all critical factors in this regard.
A Decision Support System for Assembly Line Balancing Problem
(Kadir Has Üniversitesi, 2015) Ringim, İbrahim Uba; Yücekaya, Ahmet Deniz
Assembly line balancing problems are generally considered to be complicated in real life. Like most complicated real life assembly line balancing problems obtaining a good solution is much easier than finding an optimal solution especially with big size problems. As a result, many heuristic approaches have been developed to find good optimal solutions to those problems. In this study, we develop a decision support system that solves a deterministic assembly line balancing problem using three heuristic approaches. The objectives considered are: minimizing the number of workstations, maximization of line efficiency and minimization of balance delay. Our aim is using the decision support system created; user can enter any value into the system and obtain 3 different results. The results obtained are feasible enough which shows that the decision support system works and can be able to solve even larger problems if the correct formula is applied
Designing of an Enterprise Product Innovation System for Companies
(Kadir Has Üniversitesi, 2018) Demirhan, Mehmet Özhan; Ayağ, Zeki
Today, innovation is the most decisive factor for companies to grow and gain competitive edge in the market. In particular, firms support a product innovation policy in order to be permanent in the market. Product innovation refers to the emergence of new products and the development of existing products. By means of companies' product innovation reduces expenditure; new customers win and make high profits. AHP Method with a numerical example to evaluate the projects in this system. Organizational, technical, strategic and financial criteria have been examined. In the selection of the projects, companies have given much importance to the financial and organizational criteria. This research is expected to be very useful for evaluating and selecting projects for companies.
Detection of Fraudulent Activities in Mobile Display Advertising
(Kadir Has Üniversitesi, 2017) Kaya, Safiye Şeyma; Çavdaroğlu, Burak
Most of the marketing expenditures in mobile advertising are conducted through realtime bidding (RTB) marketplaces in which ad spaces of the sellers (publishers) are auctioned for the impression of the buyers’ (advertisers) mobile apps. One of the most popular cost models in RTB marketplaces is cost per install (CPi). in a CPi campaign publishers place mobile ads of the highest bidders in their mobile apps and are paid by advertisers only if the advertised app is installed by a user. CPi cost model causes some publishers to conduct some infamous fraudulent activities known as click spamming and click injection. A click spamming publisher executes clicks for lots of users who haven’t made them. if one of these users hears about the advertised app organically (say via TV commercial) and installs it this installation will be attributed to the click spamming publisher. in click injection the fraudulent publisher’s spy app monitors the user’s activities in the app market to detect when a mobile app is downloaded on her device and triggers a click attributed to the fraudster right before the installation completes. in this study we propose a novel multiple testing procedure which can identify click spamming and click injection activities using the data of click-to-install time (CTiT) the time difference between the click of a mobile app’s ad and the first launch of the app after the installation. in a sample set of publishers we show that our procedure has a falsepositive error rate of at most 5%. Finally we run an experiment with 15263 publishers. According to the results of the experiment a total of 1474 fraudulent publishers are successfully detected.
Determination of Time-Of Prices in Electricity Markets Using Clustering Analyses
(Kadir Has Üniversitesi, 2016) Hussain, Mohsan; Çelebi, Emre
in this thesis a clustering analysis to determine the blocks (clusters) of hours for time-of-use (TOU) pricing scheme is proposed and different clustering algorithms are compared using different measures i.e. change in overall revenue mean absolute percent error and adjusted coefficient of determination (R2) from multiple linear regression analyses. Hourly electricity price and demand (load) data for two seasons (winter and summer) from Pennsylvania-New Jersey-Maryland (PJM) wholesale electricity market for 2014-2015 is used and based on detailed descriptive analyses and observations three blocks of hours (off-peak mid-peak and on-peak) are presented. in R software two clustering algorithms (agglomerative hierarchical and k-means) are employed and several clusters for summer and winter weekday hours are formed. The average of the hourly electricity prices in the same cluster for off-peak mid-peak and on-peak hours determines the TOU pricing scheme (hours in each cluster and prices for each clusters). These prices are compared to real-time pricing (RTP) rates in terms of change in overall revenue collected (price*load) and mean absolute percent error with respect to RTP rates. Finally in order to measure the significance of the TOU price and the demand relationship multiple linear regression analyses are performed. in the regression models dependent variable is the TOU price (or logarithm of it) and independent variables are the average load (or logarithm of it) of the TOU block of hours lagged TOU price and lagged TOU average load as well as categorical variables for off-peak mid-peak and on-peak hours for each TOU pricing scheme. Using Minitab software different regression models are built and adjusted R2 significance of regression coefficients and the significance of the overall model are computed. The significant models (with 95% confidence) are reported and the TOU clusters with higher adjusted R2 values are determined. Moreover in order to measure the autocorrelation effect Durbin-Watson statistics for each significant regression model are calculated and positive correlation among dependent and independent variables are reported. These analyses can be used by electricity market retailers distribution companies as well as regulatory bodies in determining TOU time blocks (clusters) and prices.
Economic and Operational Analysis of Compressed Air Energy Storage Systems
(Kadir Has Üniversitesi, 2011) Kara, Esma Sedef; Yücekaya, Ahmet Deniz
A Compressed Air Energy Storage System (CAES) is a way to store energy to be used when the demand for energy is high. in this system the air is pumped into a cavern when the power price is low and the air is used in a natural gas fired turbine to generate power when the price is high aiming to make profit from this price difference. The system can pump or generate or do both. Typically the power price is low at nights and high during the daytime. However the power and natural gas price along with the heat rate of the turbine should be included to the model to determine when the air should be pumped and when the power should be generated to maximize the revenue. in this research a mixed integer programming method is developed to determine a pumping-generation schedule for the CAES given that market and natural gas price for each hour can be forecasted. Appropriate forecasting methods are used to simulate the power and natural gas prices for the analysis. The model is coded in General Algebraic Modeling System (GAMS) and a case study is presented to validate the model. in addition to scheduling of the CAES another important contribution of this research is to develop a framework for investor companies who wish to build a CAES system. We develop 30-years long market price and natural gas price scenarios and we find annual profits through optimum scheduling of the CAES plant given that market price and natural gas prices are variable. Then we use appropriate engineering economics tools to estimate a Net Present Worth value of each different scenario for the decision makers of the investment companies.
Energy Transition Scenario Analysis for Turkey Using Long Range Energy Alternatives Planning (leap)
(Kadir Has Üniversitesi, 2019) Massaga, Daniel Julius; Kirkil, Gökhan
Fossil fuel thermal power plants constitute a large part of the Turkish electricity generation capacity. The Turkish government has been developing several energy policy documents to evaluate how various renewable energy sources of the country can be utilized optimally in the generation of electricity for the next 30 years. The study considers three scenarios in the transition to renewable energy for Turkey; the business as usual (BAU), energy conservation (EE) and renewable energy (REN) scenarios were modeled with the help of the LEAP (Long-range Energy Alternatives Planning) software. EE scenario considers the use of energy-efficient appliances across all sectors of demand while emphasizing on more efficiency in electricity production activities, whereas REN scenario considers increasing the share of the renewable energy sources as much as possible in the power generation mix. These scenarios were evaluated in terms of cost and environmental impact. The optimized energy efficiency scenario has been shown to be the optimal energy policy option for Turkey in terms of cost and environmental impact. Keywords: renewable energy, energy transition, energy efficiency, LEAP, scenario analysis
An Evaluation of Energy and Electricity in Pakistan
(Kadir Has Üniversitesi, 2016) Humaiyun, Muhammad Jasim; Yücekaya, Ahmet Deniz
Pakistan is a developing country and it can only move forward once the energy sector is secure and self sufficient. Right from the beginning the country has constantly faced energy shortages in all sectors due to incompetent policies and governence. This study frames the analysis of the current energy situation with main focus on electricity. All the factors which are hampering the growth of the energy sector are identified and potential solutions are discussed. Matching the electricity supply and demand is the ultimate goal therefore a forecast analysis (multiple regression model) based on seasonal variation in temperature is performed in order to predict the future electric consumption and help authorities take necessary actions for fulfilment. Finally a comprehensive detail is provided on the causes and problems of the energy crisis and potential solutions and reforms are provided.
A Fuzzy Ahp Approach for Financial Performance Evaluation Airline Companies
(Kadir Has Üniversitesi, 2012) Gürel, Sinem; Ayağ, Zeki
Previous researches focused on operation performance. This thesis purposes for evaluating the financial performance of the airlines. In order to achieve financial objectives to be incorporated into the financial performance of their degree. It is a method to measure the results of a company?s operations in a monetary term. The problem is modeled by multi-criteria decision making (MCDM) one. Multi criteria decision making (MCDM) is a method of the most important fields of operations research and deals with the problems that include multiple and conflicting objectives. It is obvious that when more than objective exists in the problem, making a decision becomes more complex. To solve the problem, I used the fuzzy numbers to explain their values. After that, I used a method of fuzzy multi criteria group decision making (FMCGDM) as Fuzzy Analytic Hierarchy Process (FAHP) to solve the problem of the evaluation of airlines? financial performances. At first time the decision making process of the financial performance is investigated, when financial ratios are given by a fuzzy function, they are obtained through classical methods. After that, we will discuss the main advantages of the new approach. Finally, we illustrate an experimantal model of evaluation of the three domestic airlines? financial performance in Turkey.
A Fuzzy Best-Worst Multi-Criteria Decision-Making Method for Third-Party Logistics Provider Selection
(Kadir Has Üniversitesi, 2016) Boakai, Sylivan; 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.
Location and Distribution Decisions in an Earthquake Relief Network
(Kadir Has Üniversitesi, 2015) Yenice, Zeren D.; Samanlıoğlu, Funda
In this thesis, a multi-objective mathematical model was developed in order to configure part of the earthquake relief network in Istanbul, Turkey. The aim of the mathematical model was to help decision makers decide on the locations of storage areas for relief aids as well as distribution of relief aids from these areas to temporary shelter areas while minimizing expected total distribution distance, expected total earthquake damage risk factor of storage areas and expected total unsatisfied demand penalty cost. In the model, demands of the population, coverage restrictions, and storage area capacity restrictions were taken into consideration. The data related to the potential storage areas and shelter locations were obtained from Kadıköy municipality and İstanbul metropolitan municipality (IMM). The earthquake damage risk was determined based on possible earthquake scenarios given in Japan International Cooperation Agency's (JICA) report. The mathematical model was implemented in a pilot area, Kadiköy, and sample efficient solutions were obtained in order to prepare inventory and distribution plan.
Market Price Simulations for Turkish Electricity Market Using Equilibrium Models
(Kadir Has Üniversitesi, 2014) Çakır, Hande; Çelebi, Emre
Electrical energy which is known as secondary energy sources is generated by the conversion of renewable energy sources to potential and chemical energy or is generated by variety processes of fossil fuels. Electricity is an important product in an economy and an important input for production of most of the goods and services. Electricity has unique properties such as non-storability and it has no full substitute and therefore the electricity industry is different from classical competitive industries. During the last decade new regulations and developments in the world have initiated various reform movements and a new action plan in Turkey to create a competitive market. The relevant legislation and procedures is created and specific markets are designed within this plan and vertically integrated structure of generation transmission and distribution activities are separated in this restructuring process. in this study we focus on many examples and applications in the world about electricity market equilibrium models. Since there is no market model applied in this way in Turkey it is created to simulate market prices by using GAMS software and adoption of market price simulations to Turkey's electricity markets are examined. Finally we have performed price-cost analyses and observe the welfare effects of different market structures. -- Abstract'tan.
Market-Clearing Simulations and Analyses for Turkish Electicity Market Market
(Kadir Has Üniversitesi, 2017) Şentürk Eker, Cansu; Çelebi, Emre
in this thesis current market structure of the Turkish electricity market which uses a uniform pricing system is analyzed and new market-clearing mechanisms (e.g. single or nodal pricing) are investigated for the market requirements. This has led to the development of different market-clearing models and market-price simulations that can be encountered in transition to a regional pricing model which provides market participants with greater transparency and simplicity in forecasting market outcomes. in the proposed models Turkish electricity market has been analyzed by using nine regional control areas (zones) pre-specified by Turkish Electricity Transmission Company (TETC). Based on Energy Exchange Ýstanbul transparency platform and TETC reports installed generation capacities are calculated for each region according to thirteen fuel types and seven different types of ownership. Different scenarios (e.g. seasonal peak mid-peak and off-peak) and data sets (e.g. capacity and load factors for weekdays and weekends as well as price-elastic linear demand function parameters for each region) are formed and different pricing models are formulated using a mixed complementarity problem (MCP) framework. Operation maintenance and fuel costs for each generation facility are obtained from international cost survey studies. The effects on social welfare and electricity price levels for the pricing models are examined in details using different market structures (e.g. perfectly competitive and Nash-Cournot). in MS EXCEL regional maps containing nine control areas of the transmission network are created and the results obtained from GAMS software are summarized using macros (e.g. visual basic for applications –VBA codes). in the literature such models appear for different regions and countries however it is a major shortcoming for Turkish electricity market. Hence the proposed models of this thesis will enable the analyses of decision-making process of market participants and their short/medium/long-term decisions as well as future investment plans and their impact on the market.
Minimizing the Defect Rate Using Six Sigma Dmaic Method; a Case Study in Supsan A.ş.
(Kadir Has Üniversitesi, 2016) Aslan, Nazmiye Yağmur; Ayağ, Zeki
Today manufacturing industries are highly impacted by the fast changing economic conditions. In this scenario, manufacturing industries become face to face with global competition due to globalization. The major problems of these industries are declining profit margin, customer demand for high quality product and product variety. Therefore so many organizations, especially in manufacturing sector, understand the importance of quality. Companies try to implement various strategies and innovations for enhancing their producing process. A very powerful philosophy in this area is Six Sigma. The aim of Six Sigma is to reduce cost, waste and increase productivity to produce high-quality products. So this study is applied to improve the quality of the manufactured valves, reduce the manufacturing waste and increase the yield of the manufacturing process by applying the Six Sigma methodology. Also comparison analysis is made between approaches as DMAIC, Jidoka, Value Stream Tranformation, Kaizen. In result of the analysis DMAIC is chosen for this project. DMAIC approach is a business strategy help to improve business profitability and efficiency of operations to meet customer needs and expectations. In this search discusses the quality and productivity improvement in an manufacturing enterprise which is called SUPSAN. And this search deals with an application of Six Sigma DMAIC methodology in SUPSAN to improve quality performance, to identify root causes of failure in Stellite Coating Process which is found with help of DMAIC tools. Several tools are used to identify root causes and situation analysed with help of Pareto Charts, FMEA, SIPOC, C&E Diagram. In improve phase Process Capability Analysis and Implementation Plan are made. Also improvement solutions are applied. Then with the help of tools as Control Charts, SPC Analysis results tracked, documented and controlled.In SUPSAN, the appliation of Six Sigma DMAIC methodology resulted in a reduction in the defect rate from 4.34% to 2%.
Models for Long-Term Electricity Price Forecasting for Turkish Electricity Market
(Kadir Has Üniversitesi, 2017) Özçelik, Sirun; Çelebi, Emre
in this study we have developed models for long-term electricity price forecasts for Turkish electricity market using multiple regression and time series forecasting methods. For the regression models we have firstly obtained the monthly data for demand weighted average of market-clearing electricity price (dependent variable) electricity demand hydro power production wind power production and population as well as yearly gross domestic product (GDP) and human development index (HDi) as independent variables for Turkey between December 2009 and September 2016 from the market operator's transparency database and other data sources. Secondly we have examined the effect of each of these independent variables on market-clearing electricity price and then by using time-series models long-term forecasts are obtained for all independent variables. Finally multiple-linear regression models are used to obtain forecasts for the monthly demand weighted average of electricity prices. in addition to multiple regression models several time series models such as exponential moving average (Holt-Winters model) seasonal autoregressive integrated moving average (SARiMA) and Artificial Neural Network (ANN) models are also developed. in setting up forecasting models R statistical packages and forecast tools as well as MATLAB (for ANN) are used. Long-term forecasts are made for the next 24 months starting from October 2016. Model results are evaluated according to mean absolute percentage error (MAPE) mean square error (MSE) and mean error (ME) which are commonly used error measures for evaluating forecasting results. We have found that on average around 8% of MAPE can be achieved through ANN method. This study would be useful for producers' investment decisions as well as market operator's long-term policy decisions.
Multi - Objective Location Routing Problem for Nuclear Power Plants and Nuclear Waste Disposal Centers
(Kadir Has Üniversitesi, 2011) Sezenler, Gül Ecem; Samanlıoğlu, Funda
Nuclear energy is used by many countries and has already taken its place among the future sources of energy. in Turkey nuclear energy has recently been accepted by the majority of people as an alternative energy source. As a result inspections and research have accelerated to establish a nuclear power plant. in this thesis a new multi-objective location-routing mathematical model is developed and implemented using actual data for Turkey. The model selects best locations for nuclear power plants and disposal centers from respective candidate sets and then identifies the optimal amount of nuclear waste to transport from each nuclear power plant to each disposal center. The problem includes the following objective functions: Minimizing total cost of establishing nuclear power plants and disposal centers transporting nuclear wastes between them and holding nuclear wastes minimizing total social rejection for the establishment of nuclear power plants and disposal centers and transportation of nuclear wastes minimizing total accident risk of truck minimizing total risk of earthquake damage to nuclear power plants and disposal centers and minimizing total risk of terror attacks to the locations of nuclear power plants and disposal centers. The model also includes constraints related to the capacities of disposal centers and temporary nuclear waste holding storages that might be opened inside the nuclear power plants. As the multi . objective decision making method weighted Tchebycheff method is used and weakly Pareto optimal (weakly non . dominated) solutions are obtained. The mathematical model is formulated and solved by GAMS 23.6. Data required for the thesis is obtained using the ArcGiS Spatial Analyst 10.0.
Multi-objective disaster relief logistics
(Kadir Has Üniversitesi, 2018) Samarah, Mahdi M; Agca Aktunc, Esra
Disaster relief logistics is one of the major fields of operations research. Deciding the locations of depots before the disaster by minimizing total costs and total distances between nodes of demands and these depots is the main purpose of this study. The efficiency of disaster relief logistics is expressed in terms of the total transportation cost. The other objective function is considering minimizing total accumulated time to represent efficacy to supply different number of pallets which include basic materials and necessary types of foods. Equity is represented by minimizing the percentage of unsatisfied demand achieved by balancing the capability to serve demand nodes and the ability to diminish number of pallets that would not reach the nodes. Dealing with uncertainty in both demands and distances create different scenarios for our study and the results explain how each objective function affects the logistics decisions for each scenario.

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Browsing Yüksek Lisans Tezleri by Department "Enstitüler, Lisansüstü Eğitim Enstitüsü, Endüstri Mühendisliği Ana Bilim Dalı"