2020-2021

2019-2020

 Student Name Project Title Advisor(s) Tolunay Alankaya Regression Analysis of Factors Affecting Employee Turnover Savaş Dayanık Abstract In this study, the reasons for employee turnover have been investigated. The aim was, besides, predicting the probability of an individual’s flight risk, more importantly measuring the covariates’ effects on employee turnover. Survival analysis has conducted for the problem and it gave some insights into the effects of covariates. Although we could test the significance of the covariates’ effects by using Cox proportional hazards regression model, a further investigation had to be done to finding the interaction effects of the covariates. Cox regression model has vastly used in survival analysis of many different subjects and a decent amount of papers are available in the literature which is dealing with employee turnover problem. Even though there are many types of research using that method, a challenge has arisen due to the sample size of our data. Unlike other studies, the sample size of our data has increased in years. For example, we could not easily compute the hazard rates by looking at a particular time interval since there were always new employees who have started to work for the company in that time interval. Besides that, our data is problematic in terms of missing values. For handling this problem, multiple imputation methods have used for some continuous variables in the data set. After the data has tidied, survival analysis has conducted for estimating the effects of covariates and the results of it have compared with the results of traditional methods like logistic regression. Mert Cüceloğlu Description of the Minimizers of Least Absolute Deviations Regularized with l0-norm Mustafa Pınar Abstract Using the input data points in a matrix A to express or predict the output data points given as a vector d, while using as few as possible variables, is the main focus of the study. For that purpose, an objective function is adopted where the loss function is Least Absolute Deviations and it is regularized with the sparsity of the optimal vector, i.e., the l0-norm. We shall investigate the local and global minimizers of the objective function, as well as sufficient and necessary conditions for a local minimizer to be strict. Sparsity of the vectors will be studied through bounds on regularization parameter. The findings will also be supported with numerical examples. Berkay Özşeker Predicting Employees Risk of Leaving a Company Savaş Dayanık Abstract Organizing the employee structure of a company is crucial in terms of many aspects such as, sustainability of the working environment, quality of the deliverables etc. For having a robust organizational structure, a company should know when an employee will leave so that they could be able to find another candidate for the empty position in a time period that will not affect the companies working environment. From the employee’s perspective deciding on leaving his/her position is being affected by different parameters. Having a child, prior work history, increase amount in the salary etc. Aim of this study is to predict the leaving risk of an employee with a survival analysis approach and determining related parameters and their effects on the leaving risk. For the survival analysis, an Artificial Neural Network structure which has an output layer of Cox Regression Node will be evaluated and implemented accordingly. Furthermore, some approaches used in the field of genomics will also be considered. Selin Sütçü Implementation of an Algorithm for Finding a Complete Matching with a Single Restriction Mustafa Pınar Abstract The main aim of this study is the implementation of an algorithm for finding a complete matching with a single edge subset restriction. Finding a maximum cardinality matching in graphs is a very well-known tractable problem. The variation of restricting the matching so that it uses only a limited number of edges from specified subsets results in an NP-complete problem. When the restriction is only to a single subset, the resulting problem can still be solved in polynomial time. This specific problem is the focus under the current study, and it has applications in the field of image processing. In the beginning of the study, we shall focus on implementing a known algorithm for bipartite graphs. The algorithm solves a maximum flow with minimum cost making use of several shortest path solutions in the process. Later, we shall extend this algorithm to non-bipartite graphs. The performance of our algorithms will be tested against integer programming models available for solving the restricted matching problems. Berkay Taşçı Bayesian Quality Control at Points of Sales Savaş Dayanık Abstract A prominent food company wants a point of sale quality control mechanism to monitor the quality of products on the shelves. After leaving the factories, products are prone to mishandling during transportation and stocking at warehouses. We would like to develop a Bayesian model of quality failure process of products traveling through a hierarchical network of replenishment channels from factories to stores. Then we will use the model to design effective points of sales sampling strategies to maintain high quality products at the shelves. Didar Uslu Identification and Validation of Employee Turnover Process Factors in a Manufacturing Company with Panel Data Models Savaş Dayanık Abstract Various factors play key roles in the process of leaving a job for an employee in ways of quitting, resigning or being dismissed. The employees are perceived as investments and resources for companies with the budget and effort provided in the recruitment and onboarding processes so the leaving process is a loss for the company in terms of resource which needs to be held under control and monitored. In this investigation, the main reasons behind resignation and dismissal of employees of a leading manufacturing company is examined to monitor employee commitment and predict the probability of leaving. The models are built on panel data that consists of variables such as personal, performance, education, organizational, supervisor information with marital status and commitment level of employees. Various tools and packages in the R software environment are used to build the survival and effects models that find the correlation and significance of variables with the risk analysis of leaving. The results aim to provide insight on employee portfolio of the company and suggest improvements to the recruitment and management strategy of the company’s human resources department. Fatih Selim Aktaş Optimal Sparse Solutions to Linear Systems with l1 Loss by Implicit Enumeration Mustafa Pınar Abstract Computing sparse solutions to linear systems is an ubiquitous problem in several fields such as machine learning, signal and image processing, information theory. The objective of the present project is to develop a Python code implementing an implicit enumeration algorithm to find optimal solutions to the NP-hard problem `min_x ||Ax - b||_1 s.t. number of nonzeroes(x) <= s,` for a given sparsity level s. We assume A is a m x n real matrix where m > n hence, the linear system is over determined. Most previous research efforts concentrated on the conditions under which solving the relaxation of the problem would yield a sparse solution when matrix A is underdetermined. We previously proposed another algorithm to find sparse solutions to overdetermined linear systems where l2 loss was used. Berkay Becü An Algorithm to Find Extreme Supported Non-Dominated Points of Discrete Multi Objective Optimization Problems Firdevs Ulus Abstract We consider multiobjective integer linear optimization problems and propose a modified parametric simplex algorithm for finding the set of all extreme supported nondominated points. The parametric simplex method is used for finding efficient solutions to the LP-relaxation and a corresponding weight space decomposition. In order to find the supported non-dominated points for the discrete problem, we employ cutting plane methods within the parametric simplex algorithm. The algorithm is implemented in MATLAB and tested on illustrative examples. Different variants of the algorithm will be considered, and further computational tests will be conducted. Şebnem Manolya Demir A New Selective Location Routing Problem: Educational Services for Seasonal Workers Bahat Yetiş Kara Abstract There are approximately 155 thousand seasonal workers in Turkey who temporarily migrate from their hometowns during the harvest seasons. Children of these workers mostly travel with their families, and the ones attending primary or secondary schools miss a long period of the school year. To prevent this, Turkish Ministry of Education assigns these children to a school in the migrated city. If the city schools are already operating at full capacity, or distant from the migrated harvesting field, then the ministry can construct a prefabricated school in the district. In case the children of a district are assigned to a central school, there are two transportation options. If the central school is located within two kilometers of the district, children can walk to the school; otherwise, they should be transported with a school bus. This application requires a combination of selective routing and location routing problems. In this study, we develop such a mathematical model that determines the assignments to the central schools and the school bus routes, as well as the locations of prefabricated schools. We tested the performance of our model using the data from the Southeastern provinces of Turkey that receive the largest influx of seasonal workers within the country. While this problem is inspired by the seasonal workers of Turkey, our model can be beneficial to increase the school attendance rates in other developing countries, especially for the sparsely populated rural regions without adequate schooling facilities or teaching staff. Azra Çağlasu Gürkan Time Dependent Selective Routing Problems with Time Window Bahar Yetiş Abstract Although time dependency of selective routing problems did not have studied in the literature, there are several real-life applications which show that a problem may be depend on time in terms of obtained benefit when a node is visited. This paper aims to examine selective routing problems in terms of time dependency issue by considering time windows and a mathematical model for a time dependent selective routing problem with time window is built. Egemen Elver Fairness in Knapsack Problems Özlem Karsu Abstract We consider binary knapsack problems where the decision maker has equity concerns and items have benefits in multiple categories. We first consider the deterministic problem, where all parameters are known. To ensure a balanced allocation of benefit over multiple categories, we minimize the sum of squared regrets over them and discuss alternative nonlinear and linear formulations for the square regret minimizing problem. We then perform extensive computational experiments to compare these formulations. We will now extend this analysis to see the effects of increasing parameter p on the regret allocations. Furthermore, we will consider a stochastic environment, where the item costs are uncertain. For this setting, we propose a robust programming extension so as to guarantee an equitable benefit allocation even under the worst scenario. Seyit Ulutaş Solution Algorithms for Equitable Optimization Problems Özlem Karsu Abstract We consider equitable optimization problems, which are multiobjective optimization problems involving symmetry and propose exact solution approaches that guarantee finding the whole set of equitably non-dominated solutions. We first propose an algorithm for the biobjective setting. This algorithm is based on iteratively solving two-stage scalarization models, the first stage of which maximizes the total, while the second stage ensures that the resulting solution is equitably non-dominated. We then consider extensions to three objective settings; design two algorithms and observe their performance by conducting computational experiments. For future work, we plan to explore different scalarizations and modify existing algorithms used for classical multiobjective optimization problems such that they are implementable in equitable settings.

2018-2019

 Student Name Project Title Advisor(s) Tuana Terkin Multi-Period Joint Ordering and Inspection Policy Decisions under Stochastic Demand Nesim K. Erkip Abstract In this research, we want to develop a model for the multi-period joint ordering and incoming lot inspection decisions for an item in a manufacturing context where there is stationary stochastic demand. It is presumed that there is uncertainty over the quality of the raw-material supply which consequently affects the yield for the production of the end-product. Possible incoming lot inspection decisions are “%100 inspection”, “no inspection” or “inspecting based on a specific acceptance sampling plan”. Order placements and deliveries from supplier are periodic and ordering policy is order-up-to policy. Benefit of using such a joint model is to be investigated. Seyit Emre Düzoylum Dynamic mean-variance problem: recovering time-consistency Çağın Ararat Abstract Introduced by Markowitz in 1952, obtaining a portfolio which maximizes the expected return while minimizing the risk is one of the fundamental problems of financial mathematics. The original Markowitz problem utilizes variance for the measure of risk. However, due to its insufficiency in terms of some key aspects, more adequate risk measures have found their place in the literature. Resulting from the multiple objectives of the problem, in most of the literature it has been scalarized and formulated as a single-objective optimization problem. Furthermore, due to its multi-period nature, it has been usually referred as dynamic Markowitz problem in the case of variance, or dynamic mean-risk problem otherwise. However it is well-known that the scalarized versions of mean-variance multi-objective problem does not satisfy Bellman’s principle of optimality, thus conventional methods are not appropriate for time-consistency of solutions.Recent studies on the subject have introduced new approaches to the mean-risk problem and been able to obtain time consistent solutions. One that we are most interested in, uses a coherent dynamic risk measure, proposes not scalarizing the problem but preserving its multi-objective nature and design it as a vector optimization problem (VOP), whose objective function gets extended to a set-valued function. As a result time-consistent solution to the mean-risk problem was obtained.The main objective of our study is to obtain time consistent solutions to the original, mean-variance problem by applying a similar approach and formulating the problem as a VOP. However having the variance for the measure of risk compared to a dynamic risk measure, results with some critical problems arising. The most important one is time-inconsistency of variance due to its properties. Therefore one would not be able to use the same approach as mentioned and obtain time-consistent solutions. For this reason, we are investigating a novel formulation to the problem and expecting to attain time-consistent solutions through this novel formulation combined with the VOP approach. Alper Yılmaz Input Models for Energy Commitment Decisions of a Hybrid Energy System with Pumped Hydro Storage Ayşe Selin Kocaman and Emre Nadar Abstract Systems that utilize renewable energy have the disadvantage of dealing with sources that are often irregular and intermittent. Hybrid systems aim to circumvent this issue by using various renewable energy sources and energy storage simultaneously. One such system is a hybrid system that implements a pumped-back pumped hydro storage (PHES) and a renewable energy production plant together with the objective of total profit maximization from energy commitment decisions. Formulation of this optimization problem, involving Markov decision processes and multi-stage stochastic programs, requires several input models: the electricity pricing model, the wind speed model, the streamflow model, and the solar radiation model. The aim of this project is to find the proper input models that will be used in the main profit maximization problem that provide the best representation of real life data by utilizing data analysis and other mathematical modelling techniques. Mert Çetin Heuristic Algorithm for Drone-Aided Delivery Problem Bahar Yetiş Kara Abstract In recent years, unmanned aerial vehicles (aka. drones) have become increasingly popular in commercial sector, so that delivering packages using drones along with the traditional trucks started to gain attention for logistics companies. Those companies aim to reduce their overall logistics cost, delivery times, energy consumption and further to be able to deliver to places whose transportation infrastructure is inadequate. For that purpose, a two-echelon delivery system where both trucks and drones are involved, is constructed and modeled. However, computing times grow rapidly when number of nodes increase. Thus, the goal of this study is to develop a heuristic algorithm to drone delivery problem. Deniz Şimşek An Objective Space Based Solution Approach for Multi-Objective Integer Programming Problem Firdevs Ulus and Özlem Karsu Abstract We consider multi-objective integer programming problems. We aim to design an objective space based solution algorithm that generates the whole set of non-dominated solutions. We will first consider three objective integer programming problems and then extend the algorithm for any number of objectives. A number of variants will be developed and compared through computational experiments. Duygu Söylemez Split Order Problem Alper Şen and Oya Karaşan Abstract One of the major problems that online retailers face is the split order problem. A split order occur when a retailer cannot satisfy the order by sending all the SKUs in the order in one shipment. The reason behind this is basically the unavailability of all the SKUs in the same warehouse. Because of the limited capacities of the warehouses, it is not possible to have all types of SKUs in every warehouse. The aim of the project is to minimize the number of the split orders to reduce extra packaging & shipment costs, and the delivery time. In the literature, this problem is studied in two different ways. In the first approach, it is assumed that the unit-based capacity of warehouses is unlimited, and it is only necessary to find the most appropriate assortment of SKU types for each warehouse. In the second approach, the capacity is thought as the unit-based capacity, and it is required to find the optimum amount for each SKU to stock in each warehouse. However, both versions of the problem are NP-hard. For this reason, previous studies are based on heuristic approaches. In this research project, it is aimed to come up with an optimization model which can be used to minimize the split order problem with a great number of SKUs for any version of the problem, or construct heuristic approaches that can compete with the existing literature. İrem Nur Keskin Utilizing Double Description Method in Benson’s Algorithm Firdevs Ulus Abstract Benson’s approximation algorithm is designed to solve convex vector optimization problems in the sense that it approximates the whole Pareto frontier. At each iteration, the algorithm solves a vertex enumeration and a convex optimization problem. Vertex enumeration is used to find the vertex representation of a polyhedron (current outer approximation of the Pareto frontier) given by its half-space representation. Convex optimization problem is solved for each vertex of the current polyhedron. It finds the minimum ‘distance’ between the vertex and the Pareto frontier through a given direction, which is fixed through the algorithm. The first objective of this project is to implement a vertex enumeration algorithm that uses the double-description method, to employ it as a subroutine within Benson’s algorithm, and to examine the effect of the new subroutine on it. Secondly, by using the structure of the new vertex enumeration subroutine, we aim to modify the direction parameter of the convex optimization problem that is solved in each iteration and to analyze the performance of this variant of the algorithm.

2017-2018

2016 Fall

2015 Spring

2015 Fall

2014 Spring

2014 Fall

2013 Fall

2012 Fall

 Student Name Project Title Advisor(s) Ismail Ozan Sert Carbon Sink Maximization in Budget Constrainted Afforestation Projects Nesim K. Erkip Abstract Increasing levels of greenhouse gases in the atmosphere and its implications have become an imminent concern for a plethora of parties. As a member of the developing world, Turkey is no different. Whilst environmentalists strive to maintain the ecologies intact, corporations are searching for alternative methods to ease the restrictions on their carbon footprints. Although afforestation projects are being invested in currently, they do not properly take into account the carbon aspect. This study endeavors to provide a location selection model optimizing the carbon sequestering capacities of newly planted forests under a limited budget. Natural parameters such as rainfall, soil type, compatible tree species and artificial parameters like forestfire precautions, maintenance costs and frequency are considered within the scope of the project. Utku Serhatlı Integration of Carbon Emission in Supply Chain Models Hande Yaman Abstract Global warming due to greenhouse gas(GHG) emission is one of the most controversial topics of 21st century. Concerns related to carbon emission are gaining attention at ever-increasing rate and becoming the subject of lots of heated debates. Many countries already committed to decrease their carbon emissions which ultimately force big retailer companies to reconsider their supply chain models. There is a large literature on cost minimization of supply chains which includes inventory, backorder, transportation of goods(from both customers’ and retailers’ perspective) and location. However, an emerging concept, carbon emission, is rarely included in the papers which we believe, has a huge potential to open new areas of investigation. Our aim is to develop a new model in order to integrate a carbon emission as a new component in our decision making process. Governmental decisions or company’s voluntary commitments to reduce carbon emissions plays crucial role in our analysis. The model under certain market regulations such as carbon cap, carbon tax and cap-and-trade will be examined. The regulation is an important factor to decide how to integrate carbon emission in our system i.e. either as objective or constraint. At this point we expect that transportation mode, number of stores, location of stores and stock policy are likely to play crucial role on how to structure the optimization problem. Nazlı Sönmez MARKETING IMPACT OF CARBON EMISSION AND PRICING Ülkü Gürler Abstract In this research, we consider the newsboy problem with carbon and price sensitive customers and multiple inputs. We assume that the production quantity has multiple inputs with different costs and carbon emissions. It is also assumed that the customers are environment conscious. The potential link functions that connect the random demand to carbon footprints will be investigated and the optimal production and input mixture will be determined under several demand functions. Özge Yapar Road Capacity Calculation and Its Effects on Post-Disaster Evacuation Routes and Shelter Locations Barbaros Tansel Abstract In the case of sudden environmental disasters, post-disaster evacuation is a critical issue because there is limited time to transport victims to safety, which is defined as shelters that have accommodation units, food, water and medical supply. In order to evacuate victims quickly, it is reasonable to utilize the shortest path to an available shelter. However, this approach may result in traffic congestion in some roads which yields slower speeds, longer travel times and vehicular queuing. Therefore, traffic congestion should be taken into account during the determination of evacuation routes. Indeed, since evacuation routes and location of shelters are interrelated, traffic congestion is also a relevant factor in selection of shelter locations. The aim of this study is to propose a maximum road capacity calculation that prevents traffic congestion and incorporate road capacities into evacuation route and shelter location optimization.

2011 Sping

 Student Name Project Title Advisor(s) CANSU KAPAN SAHIN Quantification of Input Model Uncertainty in Inventory Simulations Canan Güneş Çorlu MURAT TİNİÇ Comparison of Flexible Distributions in Modeling Financial Returns Canan Güneş Çorlu

2011 Fall

 Student Name Project Title Advisor(s) BURCU TEKIN Quantifying the Parameter Uncertainty in an Inventory Simulation Canan Güneş Çorlu MUSTAFA KARATAS Finding an Appropriate Method in Forecasting Intermittent Demands Alper Sen HUSEYIN GURKAN Dynamic Bidding Strategies for Multiple Keywords in Search-based Advertising Savaş Dayanık GALIP ORAN OKAN Parameter Estimation for the Generalized Lambda Distribution Canan Güneş Çorlu

2010 Spring

 Student Name Project Title Advisor(s) AMINE GIZEM OZBAYGIN A study of traffic loads and congestion in post disaster evacuation of a region via a road network Barbaros Tansel BASAK YAZAR A Different Location Routing Problem (LRP): School District Bahar Yetiş Kara MELTEM PEKER Spatial Analysis of Hub Location Bahar Yetiş Kara

2010 Fall

 Student Name Project Title Advisor(s) ONUR MUTLU Mixed Model Assembly Line Balancing Kağan Gökbayrak Mehmet R. Taner ALI INAY Linear Programming Study of the Network Flow Based Model for the P-median Problem Barbaros Tansel ALI IRFAN MAHMUTOGULLARI Inventory Management under Supply Uncertainty Nesim K. Erkip OKAN DUKKANCI Bicriteria Scheduling with deterministic machine availability constraints on a single machine Mehmet R. Tanerk NUR TIMURLENK Solving Sudoku Puzzles: Formulations, Cuts, and Bounds Emre Alper Yıldırım GIZEM SAGOL Analysis of Change Point Detection Methods Savaş Dayanık AHMET COLAK Optimal Control of One-Dimensional Random Walk with Penalty for Late Detection Savaş Dayanık

2009 Spring

 Student Name Project Title Advisor(s) FEYZA GULIZ SAHINYAZAN Heuristic Approaches for Effective Management of the Mobile Blood Donation Units at Turkish Red Crescent Bahar Yetiş Kara Mehmet R. Taner ALI INAY A Computational Study of a New Formulation of the p-Median Problem Barbaros Tansel ASLIGUL SERASU DURAN Stochastic Inventory Control with Backorders and Lead Time Quotations Mehmet Murat Fadıloğlu ELIF KETEN Dynamic Programming Approach for Portfolio Optimization in Discrete Time Savaş Dayanık ALI YESILCIMEN A Computational Study of a New Formulation of Traveling Salesman Problem Barbaros Tansel ENES BILGIN An experimental study to explore properties of optimal forests in p-median problems Barbaros Tansel YIGITALP MEDIN A Computational Study for Determining Hub Locations and Number of Aircrafts in Turkish Airlines Cargo Deliveries to Europe Bahar Yetiş Kara SERTALP BILAL CAY An Online Tool for Production Line Performance Evaluation Mehmet Murat Fadıloğlu

2009 Fall

 Student Name Project Title Advisor(s) SERCAN ALTUN Testbed for Joint Channel Allocation, Routing and Link Scheduling Research in Wireless Mesh Networks Kağan Gökbayrak CAGIN ARARAT A Lot Size – Reorder Level System for the Inventory Control of Decreasing Demand Items Nesim K. Erkip ENES BILGIN A computational study of a new formulation of p-median problem based on spanning forests Barbaros Tansel SERTALP BILAL CAY An Internet Decision Support System for Analysis of Production Lines Mehmet Murat Fadıloğlu PELIN DIREN Heuristics for Control of Wireless Mesh Networks Emre Alper Yıldırım Kağan Gökbayrak ASLIGUL SERASU DURAN Stochastic Inventory Control with Backorders and Lead Time Quotations Mehmet Murat Fadıloğlu EMRE KARA Optimal Stopping for Perpetual American Options in Discrete Time Mustafa Ç. Pınar FEYZA GULIZ SAHINYAZAN Optimization of Blood Donation via Mobile Units at Turkish Red Crescent Bahar Yetiş Kara Mehmet R. Taner OLCAY SARMAZ Exact Methods for Joint Channel Assignment, Routing and Link Scheduling in Multi-radio Wireless Mesh Networks Kağan Gökbayrak Emre Alper Yıldırım SIBEL SOZUER Joint Pricing and Order Quantity Decisions under a Customer Reservation Price Distribution Ülkü Gürler MUGE TEKIN Quickest detection of a sudden shift in the mean of a Gaussian distribution Savaş Dayanık

2008 Spring

 Student Name Project Title Advisor(s) ZIYAATTIN HUSREV AKSUT Intermodal Multicommodity Routing Problem with Scheduled Services and Piecewise Linear Transportation Costs Hande Yaman ALI DENIZ GULACTI Hub Location Problem for Intermodal and Incomplete Logistics Networks — CAGATAY KARAN Dynamic Policies for Stochastic Economic Lot Scheduling Problems Mehmet Murat Fadıloğlu GORKEM YURTLU Maximizing Blood Collection via a new Mobile Collection Network at Turkish Red Crescent Bahar Yetiş Kara Mehmet R. Taner

2008 Fall

 Student Name Project Title Advisor(s) TARDU SELIM SEPIN Optimal Replication of Options with Transaction Costs and Trading Restrictions Mustafa Ç. Pınar ZEYNEP YETIS Retailer Problem in Pricing and Ordering Decisions for Substitutable Products Nesim K. Erkip GORKEM YURTLU The Logistic Planning and Scheduling for Mobile Units of Turkish Red Crescent Bahar Yetiş Kara Mehmet R. Taner GOKHAN MEMISOGLU Producer’s Problem in a Food Supply Chain: Optimal Product Mix and Contract Type Nesim K. Erkip PINAR AYTEN GUVENC Promotion Planning with Inventory Considerations Alper Sen CAGATAY KARAN Dynamic Policies for Stochastic Economic Lot Scheduling Problems Mehmet Murat Fadıloğlu KONUR BAYRAMOGLU Manufacturer’s Mixed Pallet Design Problem Hande Yaman Alper Sen TUGCE TALI A Branch-and-Cut Algorithm for the Heterogeneous Vehicle Routing Problem Hande Yaman Mehmet R. Taner FILIZ SAYIN Inventory Control Under Dynamic Price and Lead-Time Quotations Mehmet Murat Fadıloğlu Emre Alper Yıldırım MEHMET OZCAN A Storage Layout Problem in a Spare Parts Warehouse with Multi-Command Picking Tours Barbaros Tansel CEYDA ELBASIOGLU Forecasting and Order Quantity Determination with Two Products Ülkü Gürler MERVE NAZLI ERALP Locating Detection Stations for Illegal Border Crossing Barbaros Tansel MEHMET DIYAR YATKIN A Receding Horizon Controller for Flow Shop Systems Kağan Gökbayrak