Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 2Citation - Scopus: 2Project Management in a Competitive Environment: Interdicting a CPM Based Project and Its Implications(Edp Sciences S A, 2021) Kasimoglu, Fatih; Akgun, IbrahimThere are two opponents in a classic network interdiction problem, network owner/defender and interdictor/attacker. Each side has enough information about the other's possible courses of action. While the network user wishes to run the network in an optimal way, the attacker with the limited resources tries to prevent the optimal operation of the network by interdicting the arcs/nodes of the network. In this study, we investigate project management in a competitive environment using a network interdiction approach. We assume that the project owner/manager strives to minimize the completion time of a Critical Path Method (CPM) based project while an opponent attempts to maximize the minimum completion time by inflicting some delays on project activities with available interdiction resources. Considering both discrete and continuous delay times, we develop two bi-level mixed-integer programming models for the interdictor. Using duality, we then convert the bi-level models to standard single-level models, which are solvable through standard optimization packages. We extend these models to find efficient solutions in terms of project completion time and interdiction resources from the interdictor's perspective. In this respect, we develop an algorithm to find an efficient solution set for the interdictor. Next, from project manager's standpoint, we discuss the earliest and latest scheduling times of activities in case of interdiction. Finally, we apply the developed techniques in a marketing project aiming at introducing a new product. The findings may enhance a better project management in an environment where an opponent can adversely affect the project management process by delaying some activities.Article Citation - WoS: 14Citation - Scopus: 15P-Hub Median Problem for Non-Complete Networks(Pergamon-Elsevier Science Ltd, 2018-07) Akgun, Ibrahim; Tansel, Barbaros C.Most hub location studies in the literature use a complete-network structure as an input in developing optimization models. This starting point is not necessarily from assuming that the underlying real-world network (e.g., physical network such as road and rail networks) on which the hub system will operate is complete. It is implicitly or explicitly assumed that a complete-network structure is constructed from the shortest-path lengths between origin-destination pairs on the underlying real-world network through a shortest-path algorithm. Thus, the network structure used as an input in most models is a complete network with the distances satisfying the triangle inequality. Even though this approach has gained acceptance, not using the real-world network and its associated data structure directly in the models may result in several computational and modeling disadvantages. More importantly, there are cases in which the shortest path is not preferred or the triangle inequality is not satisfied. In this regard, we take a new direction and define the p-hub median problem directly on non-complete networks that are representative of many real-world networks. The proposed problem setting and the modeling approach allow several basic assumptions about hub location problems to be relaxed and provides flexibility in modeling several characteristics of real-life hub networks. The proposed models do not require any specific cost and network structure and allow to use the real-world network and its asociated data structure directly. The models can be used with the complete networks as well. We also develop a heuristic based on the proposed modeling aproach and present computational studies. (C) 2018 Elsevier Ltd. All rights reserved.Conference Object Citation - Scopus: 2Data-Driven Methods for Optimal Setting of Legacy Control Devices in Distribution Grids(IEEE Computer Society, 2024-07-21) Savasci, Alper; Ceylan, Oǧuzhan; Paudyal, SumitThis study presents machine learning-based dispatch strategies for legacy voltage regulation devices, i.e., onload tap changers (OLTCs), step-voltage regulators (SVRs), and switched-capacitors (SCs) in modern distribution networks. The proposed approach utilizes k-nearest neighbor (KNN), random forest (RF), and neural networks (NN) to map nodal net active and reactive injections to the optimal legacy controls and resulting voltage magnitudes. To implement these strategies, first, an efficient optimal power flow (OPF) is formulated as a mixed-integer linear program that obtains optimal decisions of tap positions for OLTCs, SVRs, and on/off status of SCs. Then, training and testing datasets are generated by solving the OPF model for daily horizons with 1-hr resolution for varying loading and photovoltaic (PV) generation profile. Case studies on the 33-node feeder demonstrate high-accuracy mapping between the input feature and the output vector, which is promising for integrated Volt/VAr control schemes. © 2024 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 29A Hybrid Energy Harvesting Framework for Energy Efficiency in Wireless Sensor Networks Based Smart Grid Applications(Institute of Electrical and Electronics Engineers Inc., 2018-06) Yildiz, Huseyin Ugur; Güngör, Vehbi Çağrı; Tavli, BülentIn smart grid applications, Wireless Sensor Net-works (WSNs) which consist of battery limited sensor nodes are used on critical equipments of power distribution grids for monitoring purposes. WSN nodes have tight energy constraints hence it is important to reduce the energy consumption of sensor nodes due to harsh propagation characteristics of smart grid environment. One possible way to reduce the energy consumption is to utilize transmission power control where transmission powers are adjusted according to channel conditions. Another technique is to employ energy harvesting schemes to provide additional power for nodes by using environmental energy sources. Solar and electromagnetic energies are two possible environmental energy sources in outdoor substation environments. Solar energy can be efficiently exploited in a sunny day. On the other hand, electromagnetic energy can be used at any time. In this work, we propose a hybrid energy harvesting model that exploits both solar and electromagnetic energies and develop a Mixed Integer Programming (MIP) method to minimize the energy dissipation of sensor nodes. By using the MIP framework, we quantify the impact of the proposed hybrid energy harvesting model as well as transmission power control on the energy saving of nodes. © 2018 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 5Enerji Hasadı ve Sıkıştırmalı Algılama Yapan Gizlilik Odaklı Sualtı Kablosuz Ağlarında Ömür Analizi(Institute of Electrical and Electronics Engineers Inc., 2019-04) Uyan, Osman Gokhan; Güngör, Vehbi ÇağrıUnderwater sensor networks (UWSN) are a division of classical wireless sensor networks (WSN), which are designed to accomplish both military and civil operations, such as invasion detection and underwater life monitoring. Underwater sensor nodes operate using the energy provided by integrated limited batteries, and it is a serious challenge to replace the battery under the water especially in harsh conditions with a high number of sensor nodes. Here, energy efficiency confronts as a very important issue. Besides energy efficiency, data privacy is another essential topic since UWSN typically generate delicate sensing data. UWSN can be vulnerable to silent positioning and listening, which is injecting similar adversary nodes into close locations to the network to sniff transmitted data. In this paper, we discuss the usage of compressive sensing (CS) and energy harvesting (EH) to improve the lifetime of the network whilst we suggest a novel encryption decision method to maintain privacy of UWSN. We also deploy a Mixed Integer Programming (MIP) model to optimize the encryption decision cases which leads to an improved network lifetime. © 2020 Elsevier B.V., All rights reserved.