• Constraint programming approach for multi-resource-constrained unrelated parallel machine scheduling problem with sequence-dependent setup times 

  Yunusoğlu, Pınar; Yıldız, Seyda Topaloğlu (Taylor & Francis Ltd, 2021)

  This paper studies the multi-resource-constrained unrelated parallel machine scheduling problem under various operational constraints with the objective of minimising maximum completion time among the scheduled jobs. ...

• A meta-heuristic solution approach based on mathematical programming for tour scheduling problems involving flexible scheduling policies 

  Yıldız, Seyda Topaloğlu; Avcı, Mustafa; Yıldız, Gökalp (Gazi Univ, Fac Engineering Architecture, 2021)

  In service systems such as hospitals, banks, restaurants, airports, supermarkets, call centers, where customer demand changes during the day and between business days, the issue of how to schedule the employees is of great ...

• A Distributed depth first Search based algorithm for edge connectivity estimation 

  Uğurlu, Onur; Akram, Vahid Khalilpour; Eliiyi, Deniz Türsel (IEEE, 2020)

  The edge connectivity of a network is the minimum number of edges whose removal disconnect the network. The edge connectivity determines the minimum number of edge-disjoint paths between all nodes. Hence finding the edge ...

• Novel saturated flow boiling correlations for R600a and R717 refrigerants 

  Turgut, Oğuz Emrah; Genceli, Hadi; Asker, Mustafa; Çoban, Mustafa Turhan (Taylor & Francis Inc, 2021)

  This research study provides a detailed analysis of the two-phase flow boiling heat transfer coefficients of R600a and R717. In addition, it proposes novel saturated flow boiling heat transfer correlations for these two ...

• Improved artificial cooperative search algorithm for solving non- convex economic dispatch problems with valve-point effects 

  Turgut, Oğuz Emrah (2018)

  This paper presents Improved Artificial Cooperative Search (IACS) algorithm for solving economic dispatch problemsconsidering the valve point effects, ramp rate limits, transmission losses and prohibited operation zones. ...

• A novel chaotic manta-ray foraging optimization algorithm for thermo-economic design optimization of an air-fin cooler 

  Turgut, Oğuz Emrah (Springer International Publishing Ag, 2021)

  This research study aims to introduce chaos theory into the Manta Ray Foraging Optimization (MRFO) Algorithm and optimize a real-world design problem through the chaos-enhanced versions of this method. Manta Ray Foraging ...

• Solving time-dependent heat conduction problems using metaheuristic algorithms extended with a novel local search strategy 

  Turgut, Oğuz Emrah (Springer Int Publ Ag, 2021)

  This study proposes a novel and dexterous local search scheme for improving the exploitation phase of a generic metaheuristic algorithm. The proposed local search considers a twofold probing mechanism, which takes advantage ...

• An oppositional Salp Swarm: Jaya algorithm for thermal design optimization of an Organic Rankine Cycle 

  Turgut, Mert Sinan; Turgut, Oğuz Emrah (Springer International Publishing Ag, 2021)

  This study proposes a hybrid metaheuristic algorithm to tackle both single and multi objective optimization problems that are subjected to hard constraints.Twenty-four single objective optimization benchmark problems ...

• A New saturated two-phase flow boiling correlation based on propane (R290) data 

  Turgut, Oğuz Emrah; Çoban, Mustafa Turhan (Springer Heidelberg, 2021)

  There are plenty of literature research studies investigating two-phase heat transfer characteristics of propane under varying operational conditions. Based on the collected data retrieved from the experimental measurements, ...

• Differential evolution based global best algorithm: an efficient optimizer for solving constrained and unconstrained optimization problems 

  Turgut, Mert Sinan; Turgut, Oğuz Emrah (Springer International Publishing Ag, 2020)

  This study proposes an optimization method called Global Best Algorithm for successful solution of constrained and unconstrained optimization problems. This propounded method uses the manipulation equations of Differential ...

• Whale optimization and sine-cosine optimization algorithms with cellular topology for parameter identification of chaotic systems and Schottky barrier diode models 

  Turgut, Mert Sinan; Şağban, Hüseyin Muzaffer; Turgut, Oğuz Emrah; Özmen, Özge Tüzün (Springer, 2021)

  This research study aims to enhance the optimization accuracy of the two recently emerged metaheuristics of whale and sine-cosine optimizers by means of the balanced improvements in intensification and diversification ...

• Artificial intelligence approaches to estimate the transport energy demand in Turkey 

  Turgut, Mert Sinan; Eliiyi, Uğur; Turgut, Oğuz Emrah; Öner, Erdinç; Eliiyi, Deniz Türsel (Springer Heidelberg, 2021)

  In this study, eight parameters are selected and their historical data are collected to predict the future of the energy demand of Turkey. The initial eight parameters were the gross domestic product (GDP) of Turkey, average ...

• Island-based Crow Search Algorithm for solving optimal control problems 

  Turgut, Mert Sinan; Turgut, Oğuz Emrah; Eliiyi, Deniz Türsel (Elsevier, 2020)

  Crow Search Algorithm (CROW) is one of the members of recently developed swarm-based meta-heuristic algorithms. Literature includes different applications of this algorithm on engineering design problems. However, this ...

• A novel Master-Slave optimization algorithm for generating an optimal release policy in case of reservoir operation 

  Turgut, Mert Sinan; Turgut, Oğuz Emrah; Afan, Haitham Abdulmohsin; El-Shafie, Ahmed (Elsevier, 2019)

  Dams and reservoirs provide decision-makers and managers with appropriate control on the available water resources, allowing the implementation of various strategies for the most efficient usage of the available water ...

• Global best-guided oppositional algorithm for solving multidimensional optimization problems 

  Turgut, Mert Sinan; Turgut, Oğuz Emrah (Springer, 2020)

  This paper presents an alternative optimization algorithm to the literature optimizers by introducing global best-guided oppositional-based learning method. The procedure at hand uses the active and recent manipulation ...

• Eagle strategy based on modified barnacles mating optimization and differential evolution algorithms for solving transient heat conduction problems 

  Turgut, Mert Sinan; Turgut, Oğuz Emrah (Ismail Saritas, 2021)

  Solving time-dependent heat conduction problems through a conventional solution procedure of iterative root-finding method may sometimes cause difficulties in obtaining accurate temperature distribution across the heat ...

• Vehicle routing with compartments under product incompatibility constraints 

  Taşar, Bahar; Eliiyi, Deniz Türsel; Kandiller, Levent (Svenciliste U Zagrebu, Fakultet Prometnih Znanosti, 2019)

  This study focuses on a distribution problem involving incompatible products which cannot be stored in a compartment of a vehicle. To satisfy different types of customer demand at minimum logistics cost, the products are ...

• Customer churn prediction using deep learning 

  Seymen, Ömer Faruk; Doğan, Onur; Hızıroğlu, Abdülkadir (Springer Science and Business Media Deutschland GmbH, 2021)

  Churn studies have been used for years to achieve profitability and to establish a sustainable customer-company relationship. Deep learning is one of the contemporary methods used in churn analysis due to its ability to ...

• A multiscale algorithm for joint forecasting-scheduling to solve the massive access problem of IoT 

  Rodoplu, Volkan; Nakip, Mert; Eliiyi, Deniz Türsel; Guzelis, Cuneyt (IEEE-Inst Electrical Electronics Engineers Inc, 2020)

  The massive access problem of the Internet of Things (IoT) is the problem of enabling the wireless access of a massive number of IoT devices to the wired infrastructure. In this article, we describe a multiscale algorithm ...

• Multi-Channel Joint Forecasting-Scheduling for the Internet of Things 

  Rodoplu, Volkan; Nakip, Mert; Qorbanian, Roozbeh; Eliiyi, Deniz Türsel (IEEE-Inst Electrical Electronics Engineers Inc, 2020)

  We develop a methodology for Multi-Channel Joint Forecasting-Scheduling (MC-JFS) targeted at solving the Medium Access Control (MAC) layer Massive Access Problem of Machine-to-Machine (M2M) communication in the presence ...

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