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Yayın On the sensitivity of desirability functions for multiresponse optimization(American Institute of Mathematical Sciences, 2008-11) Aksezer, Sezgin ÇağlarDesirability functions have been one of the most important multiresponse optimization technique since the early eighties. Main reasons for this popularity might be counted as the convenience of the implementation of the method and it's availability in many experimental design software packages. Technique itself involves somehow subjective parameters such as the importance coefficients between response characteristics that are used to calculate overall desirability, weights used in determining the shape of each individual response and the size of the specification band of the response. However, the impact of these sensitive parameters on the solution set is mostly uninvestigated. This paper proposes a procedure to analyze the sensitivity of the important characteristic parameters of desirability functions and their impact on pareto-optimal solution set. The proposed procedure uses the experimental design tools on the solution space and estimates a prediction equation on the overall desirability to identify the sensitive parameters. For illustration, a classical desirability example is selected from the literature and results are given along with the discussion.Yayın Cognitive cooperative MAC with one primary and two secondary users: achievable rates and optimal power control(IEEE-INST Electrical Electronics Engineers Inc, 2014-11) Edemen, Çağatay; Kaya, OnurWe consider a three-user fading cognitive cooperative multiple access channel (MAC) with one primary and two secondary transmitters. We propose two encoding/decoding strategies with varying levels of cooperation, based on block Markov superposition encoding and backward decoding. The first is an overlay model, where the secondary users (SUs) aid the transmission of the primary user (PU) by causally decoding the PU message and forwarding it while also cooperating among each other. The second is an underlay model, where the SUs cooperate by decoding and forwarding each other's messages while treating the signal received from the PU as noise. In either case, the PU is guaranteed to operate at its maximum achievable single user rate. We characterize the achievable SU rate region for both models and maximize this region as a function of the transmit powers. The simulation results show that the SU rate region can be significantly enlarged, particularly using the overlay model.Yayın A DBN based reactive maintenance model for a complex system in thermal power plants(Elsevier Sci Ltd, 2019-10) Özgür Ünlüakın, Demet; Türkali, Busenur; Karacaörenli, Ayşe; Aksezer, Sezgin ÇağlarThermal power plants consist of several complex systems having many interacting hidden components. Any unexpected failure may lead to prolonged downtime and serious lost profits. Therefore, implementing an effective maintenance policy is crucial for this sector. Although preventive maintenance has become a more popular strategy, it does not completely prevent the need for corrective maintenance. Our aim in this study is to tackle the corrective maintenance implementation problem of a multi-component partially observable dynamic system based on a regenerative air heater in a thermal power plant. We propose eight methods having different efficiency measures with respect to time, effect and probability criteria to minimize the total number of maintenance activities in a given planning horizon. Performances of these methods are evaluated under corrective maintenance strategy using dynamic Bayesian networks. The results show that fault effect methods with best working state probability measure perform better than the others considering both the total amount of maintenance activities and also the solution time. We also point out how the methods can be implemented in real-life and how the results can be used for requirements planning. Furthermore, the proposed methods can be used for the corrective maintenance of all systems having hidden interacting components.Yayın Design of a global extremum seeking algorithm for an omni-directional robot model(Romanian Soc Control Tech Informatics, 2017-06) Dinçmen, ErkinA global extremum seeking algorithm is developed for a mobile robot model where the aim is to find the location of the most powerful signal source among the others. In other words, the control problem is to seek the global extremum point of a performance function when there are local extremas. The locations of the signal sources and signal distribution characteristics are unknown, i.e. the gradient of the performance function is unknown. The control algorithm also doesn't use any position measurement of the mobile robot itself. Henceforth, the controller is suitable for the missions where the robot moves in an unknown terrain with no GPS signal and no inertial measurements. Only the signal magnitude should be measured via a sensor mounted on the robot during the motion. A gradient estimator is designed to determine the motion direction towards the extremum point. When a local extremum is found, the robot will continue its search for another extremum points. Once each extremums have been visited, the robot will compare the signal levels on each source and identify the global extremum i.e. the most powerful signal source. In the absence of any position measurements, the robot can move towards the global extremum by repeating its motion history backwards. In the literature, this is the first global extremum seeking algorithm that has been developed for an omni-directional mobile robot model. Via the simulation studies it has been shown that the control algorithm can seek and find both stationary and non stationary signal sources and it can find the global extremum point when there are local extremas.Yayın A mathematical model for perishable products with price- and displayed-stock-dependent demand(Elsevier Ltd, 2016-12) Önal, Mehmet; Yenipazarlı, Arda; Kundakçıoğlu, Ömer ErhunWe introduce an economic order quantity model that incorporates product assortment, pricing and space-allocation decisions for a group of perishable products. The goal is to maximize the retailer's profit under shelf-space and backroom storage capacity constraints. We assume that the demand rate of a product is a function of the selling prices and the displayed stock levels of all the products in the assortment. We propose a Tabu Search based heuristic method to solve this complex problem.Yayın Optimal primary-secondary user pairing and power allocation in cognitive cooperative multiple access channels(IEEE, 2014) Bakşi, Saygın; Kaya, OnurWe develop jointly optimal power control and primary-secondary user partnering strategies for a cognitive cooperative multiple access channel with K primary and K secondary users. For each primary user, a cooperating secondary user is assigned. We consider both underlay and overlay modes for cognition/cooperation. In overlay mode, each secondary user decodes and relays part of its assigned primary user's message, and simultaneously transmits its own independent message, while ensuring the primary user achieves at least its single user capacity with power control. The encoding is based on channel adaptive block Markov superposition coding, where the powers assigned to primary and secondary user codewords are optimized so as to maximize either the system's sum rate, or the sum of secondary users' rates. In underlay mode, each secondary user employs independent signalling and allocates its power to maximize its own rate, without decreasing its assigned primary user's rate. The partnering problem for either mode is reduced to a maximum weighted matching (MWM) problem on a bipartite graph, and solved jointly optimally with the power allocation problem.Yayın Incremental construction of rule ensembles using classifiers produced by different class orderings(IEEE, 2016) Yıldız, Olcay Taner; Ulaş, AydınIn this paper, we discuss a novel approach to incrementally construct a rule ensemble. The approach constructs an ensemble from a dynamically generated set of rule classifiers. Each classifier in this set is trained by using a different class ordering. We investigate criteria including accuracy, ensemble size, and the role of starting point in the search. Fusion is done by averaging. Using 22 data sets, floating search finds small, accurate ensembles in polynomial time.Yayın Design and implementation of wideband microwave amplifiers based on Normalized Gain Function(Institute of Electrical and Electronics Engineers Inc., 2014) Köprü, Ramazan; Kılınç, Sedat; Aksen, Ahmet; Yarman, Bekir Sıddık BinboğaIn this work, we introduce the design and implementation of wideband microwave amplifiers based on "Normalized Gain Function (NGF)" method. Normalized Gain Function is defined as the ratio of desired shape or frequency response of the gain function of the amplifier to be designed and shape of the transistor forward gain function. Synthesis of input/output matching networks (IMN/OMN) of the amplifier require target gain curves as the functions of normalized gain function to be tracked in two sequential nonlinear optimization processes. A prototype low power amplifier circuit is produced and measured to show the usability of the design approach.Yayın Extremum seeking dead-zone pre-compensator for an industrial control system(Walter De Gruyter GMBH, 2018-06-26) Dinçmen, ErkinPID type industrial controllers such as PI, PD, PID are mature control algorithms and they are intensively used in industry due to their simplicity and easily implementability. However, they start to fail when there is an unknown or unpredictable nonlinear behavior in the plant or actuator. In this paper, a novel compensation algorithm is proposed for PD type industrial control systems, which possess an unknown dead-zone nonlinearity. An extremum-seeking technique is utilized in the compensation algorithm. The aim is to propose a new, effective and robust compensator which can be added easily to an existing industrial controller without any need to change/retune the controller settings/parameters. It is shown that by adding the compensator to an existing PD control system, the sensitivity of the controller to the dead-zone nonlinearity is removed.Yayın A stochastic risk-averse framework for blood donation appointment scheduling under uncertain donor arrivals(Springer, 2020-12) Yalçındağ, Semih; Baş Güre, Seda; Carello, Giuliana; Lanzarone, EttoreBlood is a key resource in all health care systems, usually drawn from voluntary donors. We focus on the operations management in blood collection centers, which is a key step to guarantee an adequate blood supply and a good quality of service to donors, by addressing the so-called Blood Donation Appointment Scheduling problem. Its goal is to employ appointment scheduling to balance the production of blood units between days, in order to provide a reasonably constant supply to transfusion centers and hospitals, and reduce non-alignments between physicians' working times and donor arrivals at the collection center. We consider a two-phase solution framework taken from the literature, in which a deterministic linear programming model preallocates time slots to different blood types and a prioritization policy assigns the preallocated slots to the donors when they make a reservation. However, the problem is stochastic in nature and requires consideration of the uncertain arrivals of non-booked donors. In this work, to include the uncertain arrivals, we propose three stochastic counterparts of the preallocation model based on a risk-neutral objective and two risk-averse objectives, respectively, where the Conditional Value-at-Risk is considered as the risk measure in the last two methods. The resulting stochastic frameworks have been tested considering the historical data of one of the largest Italian collection centers, the Milan Department of the "Associazione Volontari Italiani Sangue" (AVIS). Results show the effectiveness of the stochastic models, especially the mean-risk one, and the need to include the uncertainty of arrivals in order to better balance the production of blood units.
