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Permanent URI for this communityhttps://hdl.handle.net/20.500.14288/2
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Publication Metadata only An exact algorithm for integrated planning of operations in dry bulk terminals(Pergamon-Elsevier Science Ltd, 2019) N/A; Department of Industrial Engineering; Ünsal, Özgür; Oğuz, Ceyda; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; 328856; 6033We consider integrated planning problem of export dry bulk terminals. This problem consists of three important operations: (i) berth allocation, (ii) reclaimer scheduling, and (iii) stockyard allocation, and includes tidal time windows, multiple stocking pads and non-crossing of reclaimers. We exploit relationships among these operations to decompose this complex problem and propose a logic-based Benders decomposition algorithm. Master and subproblems are modeled with mixed-integer programming and constraint programming, respectively, such that complementary strengths of these programming paradigms are utilized. Computational experiments show that the proposed method can effectively solve the integrated problem for up to two weeks of planning horizon.Publication Open Access Coordinate interleaved orthogonal design with media-based modulation(Institute of Electrical and Electronics Engineers (IEEE), 2021) Yldırım, İbrahim; Altunbaş, İbrahim; Department of Chemical and Biological Engineering; Başar, Ertuğrul; Faculty Member; Department of Chemical and Biological Engineering; College of Engineering; 149116In this work, we propose a new multiple-input multiple-output (MIMO) concept, which is called coordinate interleaved orthogonal design with media-based modulation (CIOD-MBM). The proposed two novel CIOD-MBM schemes provide improved data rates as well as diversity gain while enabling hardware simplicity using a single radio frequency (RF) chain. Moreover, using the equivalent channel model, a reduced complexity can be obtained for maximum likelihood (ML) detection of the proposed system. Using computer simulations, it is shown that CIOD-MBM schemes provide remarkably better performance against the conventional MBM and CIOD systems.Publication Metadata only Hub network design problem with capacity, congestion, and stochastic demand considerations(Informs, 2023) Bayram, Vedat; Farham, M. Saleh; Department of Industrial Engineering; Yıldız, Barış; Department of Industrial Engineering; College of EngineeringOur study introduces the hub network design problem with congestion, capacity, and stochastic demand considerations (HNDC), which generalizes the classical hub location problem in several directions. In particular, we extend state-of-the-art by integrating capacity acquisition decisions and congestion cost effect into the problem and allowing dynamic routing for origin-destination (OD) pairs. Connecting strategic and operational level decisions, HNDC jointly decides hub locations and capacity acquisitions by considering the expected routing and congestion costs. A path-based mixed-integer second-order cone programming (SOCP) formulation of the HNDC is proposed. We exploit SOCP duality results and propose an exact algorithm based on Benders decomposition and column generation to solve this challenging problem. We use a specific characterization of the capacity-feasible solutions to speed up the solution procedure and develop an efficient branch-and-cut algorithm to solve the master problem. We conduct extensive computational experiments to test the proposed approach's performance and derive managerial insights based on realistic problem instances adapted from the literature. In particular, we found that including hub congestion costs, accounting for the uncertainty in demand, and whether the underlying network is complete or incomplete have a significant impact on hub network design and the resulting performance of the system.Publication Open Access Index modulation based coordinate interleaved orthogonal design for secure communications(Institute of Electrical and Electronics Engineers (IEEE), 2021) Yıldırım, İbrahim; Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Özpoyraz, Burak; Faculty Member; Master Student; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 149116; N/AIn this paper, we propose a physical layer security scheme that exploits a novel index modulation (IM) technique for coordinate interleaved orthogonal designs (CIOD). Utilizing the diversity gain of CIOD transmission, the proposed scheme, named CIOD-IM, provides an improved spectral efficiency by means of IM. In order to provide a satisfactory secrecy rate, we design a particular artificial noise matrix, which does not affect the performance of the legitimate receiver, while deteriorating the performance of the eavesdropper. We derive expressions of the ergodic secrecy rate and the theoretical bit error rate upper bound. In addition, we analyze the case of imperfect channel estimation by taking practical concerns into consideration. It is shown via computer simulations that the proposed scheme outperforms the existing IM-based schemes and might be a candidate for future secure communication systems.Publication Open Access Machine learning based channel modeling for Vehicular Visible Light Communication(Institute of Electrical and Electronics Engineers (IEEE), 2021) Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Turan, Buğra; Faculty Member; Other; PhD Student; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 7211; N/AVehicular Visible Light Communication (VVLC) is preferred as a vehicle-to-everything (V2X) communications scheme due to its highly secure, low complexity and radio frequency (RF) interference free characteristics, exploiting the line-of-sight (LoS) propagation of visible light and usage of already existing vehicle light emitting diodes (LEDs). Current VVLC channel models based on deterministic and stochastic methods provide limited accuracy for path loss prediction since deterministic methods heavily depend on site-specific geometry and stochastic models average out the model parameters without considering environmental effects. Moreover, there exists no wireless channel model that can be adopted for channel frequency response (CFR) prediction. In this paper, we propose novel framework for the machine learning (ML) based channel modeling of the VVLC with the goal of improving the model accuracy for path loss and building the CFR model through the consideration of multiple input variables related to vehicle mobility and environmental effects. The proposed framework incorporates multiple measurable input variables, e.g., distance, ambient light, receiver inclination angle, and optical turbulence, with the exploitation of feed forward neural network based multilayer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and decision tree based Random Forest learning methods. The framework also includes data pre-processing step, with synthetic minority over-sampling technique (SMOTE) data balancing, and hyper-parameter tuning based on iterative grid search, to further improve the accuracy. The accuracy of the proposed ML based channel modeling is demonstrated on the real-world VVLC vehicle-to-vehicle (V2V) communication channel data. The proposed MLP-NN, RBF-NN, and Random Forest based channel models generate highly accurate path loss predictions with 3.53 dB, 3.81 dB, 3.95 dB root mean square error(RMSE), whereas the best performing stochastic model based on two-term exponential fitting provides prediction accuracy of 7 dB RMSE. Moreover, MLP-NN and RBF-NN models are demonstrated to predict VVLC CFR with 3.78 dB and 3.60 dB RMSE, respectively.Publication Metadata only Package routing problem with registered couriers and stochastic demand(Pergamon-Elsevier Science Ltd, 2021) Department of Industrial Engineering; Yıldız, Barış; Faculty Member; Department of Industrial Engineering; College of Engineering; 258791Providing the crowd-sourced delivery capacity and hence enabling the practice, occasional couriers (OC) are the most critical resource in crowd-shipping (CS). therefore, As well as establishing and retaining a solid OC base, using the OC trips efficiently is of utmost importance for the viability of the CS applications. one auspicious idea to enhance the efficiency, i.e., cover a larger demand set with the available OC trips, is to use transshipments (deliver packages with a coordinated effort of OCs) and collect OC trip information in advance to efficiently coordinate them, which gives rise to the package routing problem with registered couriers (PRP-R) we introduce in this paper. in particular, we study a CS model in which the couriers register their trips in advance while the express shipping demands arrive through a stochastic process, and the network management needs to dynamically decide package-courier assignments to carry out deliveries in the most efficient way. We develop a novel rolling horizon algorithm to solve this challenging problem in real-time, which explicitly considers the limited OC capacities and use of a back-up delivery capacity (company-owned or third party provided) to ensure the service quality. Beyond the classical rolling horizon approaches, the suggested methodology uses a novel Monte Carlo procedure to take anticipated future system conditions into account, and thus can provide package-courier assignments that have almost the same cost with the optimal solution of the static version of the problem where all demand arrivals are known a-priory. the comprehensive numerical experiments attest to the efficacy of our methodology for the real-time management of the CS operations and provide significant managerial insights about the design of CS networks.Publication Open Access Provably high-quality solutions for the meal delivery routing problem(The Institute for Operations Research and the Management Sciences (INFORMS), 2019) Savelsbergh, Martin; Department of Industrial Engineering; Yıldız, Barış; Faculty Member; Department of Industrial Engineering; College of Engineering; 258791Online restaurant aggregators with integrated meal delivery networks have become more common and more popular in the past few years. Meal delivery is arguably the ultimate challenge in last-mile logistics: a typical order is expected to be delivered within an hour (much less if possible) and within minutes of the food becoming ready. We introduce a novel formulation for a meal delivery routing problem (in which we assume perfect information about order arrivals) and develop a simultaneous column- and row-generation method for its solution. The analysis of the results of an extensive computational study, using instances derived from real-life data, demonstrates the efficacy of the solution approach, and provides valuable insights into, among others, the (potential) benefits of order bundling, courier-shift scheduling, and demand management.Publication Metadata only Public transport-based crowd-shipping with backup transfers(Informs, 2022) N/A; N/A; Department of Industrial Engineering; Kızıl, Kerim Uygur; Yıldız, Barış; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 258791With the rising urbanization and booming e-commerce, traditional last-mile delivery systems fail to satisfy the need for faster, cheaper, and more environmentally friendly deliveries. Several new approaches are put forward as an alternative to classical delivery systems in this regard, yet none of them offers the same level of flexibility, capacity, reliability, and managerial control by itself. This paper proposes a new last-mile delivery model that combines several new approaches and technologies to address this issue. More precisely, we suggest using public transit as a backbone network completed by automated service points, crowd-shipping, and backup transfers with zero-emission vehicles to provide a low-cost and environmentally friendly express delivery service. The design problem for the envisioned system is formulated as a two-stage stochastic program, and a branch-and-price (BP) algorithm is devised to solve it. Taking advantage of the nearly decomposable structure that would emerge in possible real-world applications, our study presents the first example of using decomposition branching in a BP framework to enhance computational efficiency. Extensive computational studies and simulations with real-world data reveal valuable managerial insights for the proposed system and attest to the efficacy of the suggested methodology.Publication Open Access Spectrum-aware and energy-adaptive reliable transport for internet of sensing things(Institute of Electrical and Electronics Engineers (IEEE), 2018) Biçen, A. Ozan; Ergül, Özgür; Department of Electrical and Electronics Engineering; Akan, Özgür Barış; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and EngineeringWireless sensors equipped with cognitive radio, i.e., cognitive radio sensor networks (CRSN), can access the spectrum in an opportunistic manner and coexist with licensed users to mitigate the crowded spectrum problem and provide ubiquitous remote event monitoring and tracking for cyber-physical systems. In this paper, a novel transport layer protocol for CRSN, spectrum-aware energy-adaptive reliable transport protocol is presented to enable energy-adaptive collaborative event sensing in spectrum-scarce cyber-physical systems. To the best of our knowledge, this is the first attempt to specifically devise a reliable event transport scheme for CRSN.Publication Metadata only Transshipment network design for express air cargo operations in China(Elsevier B.V., 2023) Savelsbergh, Martin; Dogru, Ali K.; Department of Industrial Engineering; Yıldız, Barış; Department of Industrial Engineering; College of EngineeringWe introduce a novel multimodal (ground and air transportation) network design model with transshipments for the transport of express cargo with heterogeneous service classes (i.e., next morning delivery, and next day delivery). We formulate this problem using a novel path-based mixed-integer program which seeks to maximize the demand (weight) served. We investigate the value of the proposed transshipment network under various operational conditions and by benchmarking against a direct shipment network and a network with a single transshipment point which mimics a classical star-shaped hub-and-spoke network. Our extensive computational study with real-world data from ShunFeng (SF) Express reveals that the integration of ground and air transportation improves the coverage and that transshipment enables serving a large number of origin–destination pairs with a small number of cargo planes. Importantly, we show that by simplifying handling, i.e., employing cross-docking rather than time-consuming sortation, a transshipment network can transport express cargo fast enough to meet demanding delivery deadlines. Finally, we find that increasing the efficiency of intra-city operations and extending the nightly operating time window are the most effective operational adjustments for further improving the performance of the proposed transshipment network.