Person: ÇAVDUR, FATİH
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ÇAVDUR
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FATİH
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Publication Allocation of temporary disaster-response facilities for relief-supplies distribution: A stochastic optimization approach for afterdisaster uncertainty(Asce-amer Soc Civil Engineers, 2021-02-01) Çavdur, Fatih; Köse-Küçük, Merve; Sebatli, Aslı; ÇAVDUR, FATİH; KÖSE KÜÇÜK, MERVE; Sebatli, Aslı; Bursa Uludağ Üniversitesi/Endüstri Mühendisliği Bölümü; 0000-0001-8054-5606; 0000-0001-6877-2937; 0000-0002-9445-6740; AAC-2099-2020; AAG-9471-2021; AAE-4504-2019; JYP-7925-2024In disaster operations management, the prepositioning of relief supplies might improve the efficiency of the corresponding operations significantly. Developing new strategies based on this idea for relief-supplies distribution operations might also provide great benefits because it allows the utilization of local resources in the critical time period after the occurrence of a disaster. Such local resources can be utilized to serve disaster victims until the arrivals of their central counterparts, usually organized by a governmental humanitarian organization. It is noted that two-stage stochastic programs provide a nice modeling framework for allocating disaster-response facilities for relief-supplies distribution in which facility allocation and service decisions are performed in the first and second stages, respectively. Although such a modeling framework is employed in a recent study for allocating temporary disaster-response facilities, it has some limitations in terms of representing the stochastic nature of the problem. In this paper, to point out these limitations, we extend the approach presented in the corresponding study by increasing the number of scenarios in the stochastic program via a more comprehensive scenario construction approach that considers the destructive effects of a disaster. In particular, we compute arrival time probabilities conditioned on disaster levels by modifying the mode parameter of a discrete-triangular mass function accordingly to represent different afterdisaster situations in the proposed scenario construction approach. A detailed case study to illustrate the extended approach is presented. It is noted from the results that considering the destructive effects of a disaster allows us to make new observations about the problem.Publication A mathematical programming model for using dynamically-positioned-rework stations for performing parallel tasks in assembly line balancing(University of Cincinnati Industrial Engineering, 2021) Çavdur, Fatih; Sebatlı Sağlam, Aslı; Kaymaz, Elif; ÇAVDUR, FATİH; Sebatlı Sağlam, Aslı; Kaymaz, Elif; 0000-0001-8054-5606; 0000-0002-9445-6740; AAG-9471-2021; AAC-2099-2020; FEI-2659-2022In this study, a mathematical programming model for using dynamically-positioned-rework stations for performing parallel tasks in assembly line balancing is proposed. We first introduce a nonlinear programming model, which is quadratic in constraints resulting from the modeling of the parallel task assignment and dynamic positioning of the rework station. We also establish some novel logical conditions in the model building process while deriving the proposed formulation. In the next step, we present appropriate variable transformations for linearization to take advantage of the algorithms for solving linear programs by noting that the quadratic expressions of the model are present as either the multiplications of binaries or binaries multiplied by continuous variables. After implementing the corresponding variable transformations, the model is transformed to a linear-mixed-integer program. A numerical example is then presented using the resulted linear model for illustration. We also perform some computational experiments using sample problems from the related literature to analyze the performance of the model.Publication A two-phase binary-goal programming-based approach for optimal project-team formation(Taylor & Francis, 2019-04-03) Çavdur, Fatih; Sebatlı, Aslı; Köse-Küçük, Merve; Rodoplu, Çağla; ÇAVDUR, FATİH; Sebatlı, Aslı; KÖSE KÜÇÜK, MERVE; Rodoplu, Çağla; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.; 0000-0001-8054-5606; 0000-0002-9445-6740; 0000-0001-6877-2937; JYP-7925-2024; AAG-9471-2021; AAC-2099-2020; AAE-4504-2019; DOA-2442-2022This study presents a two-phase binary-goal programming-based approach for solving a novel system design project-team formation problem which involves several restrictions and requirements as well as the preferences of the potential team members. The problem instance considered in this study basically includes two types of allocations, as the allocations of students and academic advisers, which are performed in the first and second phase of the proposed solution approach, respectively. Although it represents a particular case as represented in this study, it can be easily generalised to be used for solving similar project-team formation problems. We implement our methodology on a real-life problem in an academic institution and compare our solutions to the real-life allocations performed manually. It is noted that, in terms of satisfying the goals of the problem, our approach significantly outperforms the real-life allocations. In addition, computational results show our model's ability to solve similar-sized real-life problems in reasonable time periods on an average personal computer, implying its potential for significant savings in terms of the human resources available.Publication A scenario-based decision support system for allocating temporary-disaster-response facilities(Gazi Üniversitesi, Mühendislik Mimarlık Fakültesi, 2021-01-01) Çavdur, Fatih; Sebatli-Sağlam, Aslı; Köse-Küçük, Merve; ÇAVDUR, FATİH; Sebatli-Sağlam, Aslı; KÖSE KÜÇÜK, MERVE; Bursa Uludağ Üniversitesi/Endüstri Mühendisliği Bölümü; 0000-0002-9445-6740; 0000-0001-6877-2937; AAC-2099-2020; JYP-7925-2024; AAE-4504-2019Disaster operations management is carried out in a chaotic environment under uncertainty and time pressure. Therefore, it is necessary to use information and communication technologies in the decision making processes. In this study, a standalone decision support system is developed for temporary-disaster-response facilities allocation for relief supplies distribution as one of the important problems in disaster operations management. The decision support system consists of three main components as its database, decision engine and user interface. It is noted that the decision support system allows decision makers to allocate temporary-disaster-response facilities under many different disaster situations by utilizing a scenario-based approach. Thus, disaster operations managers are given the opportunity to create different scenarios and analyze the results that will help them make critical decisions before and during the disaster. In the scenario definition process, in addition to taking into account different values of affected population rate and planning period, some model configurations consisting of the combinations of various problem parameters are also defined. Although it is illustrated with a specific example case in this paper, the flexibility of the system allows its users to consider other cases with different scenarios. Due to the user-friendly interface of the decision support system, reports of the results obtained for various disaster scenarios are presented to the user in an understandable way. The proposed system might be a useful tool to help decision makers in allocating temporary-disaster-response facilities for relief supplies distribution.Publication Solving the unrelated parallel batch machine scheduling problem with mixed-integer programming(Gazi Üniversitesi, 2021-12-31) Bakir, Merve; Sebatli-Saglam, Asli; Cavdur, Fatih; ÇAVDUR, FATİH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi.; 0000-0003-3300-8773; 0000-0002-9445-6740; JYP-7925-2024; AAC-2099-2020In this study, the problem of scheduling jobs with arbitrary sizes and non-zero release times on a set of unrelated parallel batch processing machines with different capacities is discussed. Three mixed-integer programming models with different objective functions are developed to solve the problem. Corresponding models aim at minimizing (i) the total flow time, (ii) the makespan and (iii) the total tardiness, respectively, which are considered to be among the most important objectives in scheduling problems. In order to test the validity and applicability of the proposed solution approach, different datasets are generated using some rules in the literature. The results obtained by solving the mathematical programming models with these data sets are analyzed in terms of some performance parameters.Publication A spreadsheet-based decision support tool for temporary-disaster-response facilities allocation(Elsevier, 2020-04-01) Çavdur, Fatih; Sebatlı Sağlam, Aslı; Köse-Küçük, Merve; ÇAVDUR, FATİH; Sebatlı Sağlam, Aslı; KÖSE KÜÇÜK, MERVE; Bursa Uludağ Üniversitesi/Endüstri Mühendisliği Bölümü; 0000-0001-8054-5606; 0000-0002-9445-6740; 0000-0001-6877-2937; AAC-2099-2020; AAE-4504-2019; JYP-7925-2024; AAG-9471-2021In this study, we present a spreadsheet-based decision support tool for allocating temporary-disaster-response facilities for relief supplies distribution. The tool developed in this study mainly consists of three main components as its database, decision engine and user interface. We develop the tool to run on a spreadsheet environment rather than producing a standalone application by aiming at providing more convenience for the user to perform tasks such as data manipulation and reporting. The paper also presents an example case for illustration. The tool allows the user (i.e., decision makers) to allocate temporary-disaster-response facilities under many different after-disaster situations (scenarios) considering the possible uncertainties to occur after a disaster (i.e., different affected population rates, planning periods etc.). Although we present some example cases in the paper for illustration purposes, the flexibility of the tool allows its users to consider other cases with many other scenarios. The tool can be used to help decision makers for allocating temporary-disaster-response facilities for planning relief supplies distribution operations.Publication Analysis of relief supplies distribution operations via simulation(Gazi Üniversitesi, 2019-02-12) Sebatlı, Aslı; Çavdur, Fatih; Sebatlı, Aslı; ÇAVDUR, FATİH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.; 0000-0002-9445-6740; 0000-0001-8054-5606; JYP-7925-2024; AAG-9471-2021; AAC-2099-2020In this study, we develop a simulation model to analyze the simultaneous usage of both local and global resources in relief supplies distribution operations. In order to generate the scenarios of the simulation model, we use the significant earthquakes archive of the United States Geological Survey. We estimate earthquake intensity using the magnitude, depth and distance to the epicenter of an earthquake via an artificial neural network. In relation to estimated earthquake intensity, we determine the affected population rate and the disaster level. In addition to these two parameters, the number of pre-positioned Temporary-Disaster-Response facilities is presented as another scenario parameter. Our simulation model includes two main components as global and local, where we model the arrivals of the resources of central humanitarian organizations and local relief supplies distribution operations in the global and local components, respectively. Using the simulation model, inventory levels of Temporary-Disaster-Response facilities are controlled simultaneously with the relief supplies distribution operations of central humanitarian organizations. Proposed simulation model is run with the scenarios generated and the results are analyzed in terms of some performance measures.Publication Analyzing the use of rework stations for parallel tasks in assembly line balancing via mathematical programming and simulation(Gazi Univ, 2022-03-01) Kaymaz, Elif; Çavdur, Fatih; ÇAVDUR, FATİH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Anabilim Dalı.; JYP-7925-2024In assembly lines, rework stations are generally used for reprocessing defective items. On the other hand, using rework stations for this purpose only might cause inefficient usage of the resources in this station especially if the defective rate of the assembly line is low. In this study, first, a mixed-integer programming model for cycle time minimization is presented by considering the use of rework stations for parallel tasks. By linearizing the non-linear constraint about parallel tasks using a variate transformation, the model is transformed to a linear-mixed-integer form. Secondly, a novel simulation model is developed in the study for validating the results obtained using the integer programming model by incorporating stochastic problem components. Using the developed model, two sample problems are simulated and the applicability of the integer programming models results are analyzed.Publication Earthquake intensity estimation via an artificial neural network: Examination of different network designs and training algorithms(Gazi Üniversitesi, 2022-01-01) Sağlam, Aslı Sebatlı; Çavdur, Fatih; Sağlam, Aslı Sebatlı; ÇAVDUR, FATİH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.; 0000-0002-9445-6740; AAC-2099-2020; JYP-7925-2024Purpose: We aim to estimate the earthquake intensity via an artificial neural network. Theory and Methods: We obtain significant earthquakes data from the database of the United States Geological Survey. An artificial neural network is developed using the MATLAB Neural Network Toolbox. We first determine an appropriate network design by estimating earthquake intensity with different artificial neural network designs and then the best training algorithm for the appropriate network design by evaluating different algorithms for the corresponding network design. Results: In terms of the average performance parameters, the network structure with two hidden layers and five and ten hidden neurons in each respective layer is determined as the most appropriate design. We observe the best results in terms of performance parameters by using the Levenberg-Marquardt training algorithm with Bayesian Regularization for the corresponding network structure. Conclusion: Earthquake intensity estimation is critical in predicting the impact that will occur after a disaster. In this study, we estimate earthquake intensity via an artificial neural network. In future studies, associated with earthquake intensity, we can estimate the number of casualties, damages to the buildings, economic loss and so on. Integrating earthquake intensity estimation into other disaster operation management studies may be another future study direction.Publication Dyeing behavior of enzyme and chitosan-modified polyester and estimation of colorimetry parameters using random forests(Korean Fiber Soc, 2023-02-13) Toprak-Çavdur, Tuba; ANİŞ, PERVİN; TOPRAK ÇAVDUR, TUBA; Anis, Pervin; Bakır, Merve; Çavdur, Fatih; ÇAVDUR, FATİH; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Tekstil Mühendisliği Bölümü.; Bursa Uludağ Üniversitesi/Orhaneli Meslek Yüksek Okulu.; 0000-0001-8475-3197; 0000-0003-3300-8773; 0000-0002-9445-6740; AAC-2099-2020; B-5740-2017; JYP-7925-2024Dyeing of the crystalline structure necessitates a process with a disperse dye either at high temperatures or with a carrier due to its compact and non-ionic structure of polyester. In this study, in order to eliminate these limitations and develop more environmentally friendly dyeing processes, the dyeability of polyester under different conditions with reactive, direct, and acid dyes after surface modifications with enzyme and chitosan was investigated. In addition to the corresponding physical experiments, CIELAB and color strength values were also estimated using random forests. The results of the physical experiments showed that the surface modifications conducted with enzyme and chitosan significantly increased the color depths obtained in dyeing for reactive, direct, and acid dyes, especially at pH 4.5. This was explained by the potentially protonated amine groups in acidic medium of chitosan could have attracted large amounts of anionic dye molecules with physical forces. The highest color depths were obtained from acid dyeing. Washing fastness of the pre-treated and dyed fabrics (except the acid-dyed fabrics) decreased with the shift of the bath pH values to the acidic region. In the next phase of the study, we implemented random forests to estimate CIELAB and color strength values. We considered different random forest designs and trained each design ten times to observe the performance of the corresponding topology. The results of the computational experiments showed that the estimation performance of the random forests is quite satisfactory (with R-values greater than 99%) and random forests could be used to estimate CIELAB and color strength values successfully.