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Publication Metadata only A bi-criteria optimization model to analyze the impacts of electric vehicles on costs and emissions(Elsevier, 2017) N/A; N/A; Department of Industrial Engineering; Kabatepe, Bora; Türkay, Metin; Master Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956Electric vehicles (EV) are emerging as a mobility solution to reduce emissions in the transportation sector. The studies environmental impact analysis of EVs in the literature are based on the average energy mix or pre-defined generation scenarios and construct policy recommendations with a cost minimization objective. However, the environmental performance of EVs depends on the source of the marginal electricity provided to the grid and single objective models do not provide a thorough analysis on the economic and environmental impacts of EVs. In this paper, these gaps are addressed by a four step methodology that analyzes the effects of EVs under different charging and market penetration scenarios. The methodology includes a bi-criteria optimization model representing the electricity market operations. The results from a real-life case analysis show that EVs decrease costs and emissions significantly compared to conventional vehicles.Publication Metadata only Bicriteria optimization approach to analyze incorporation of biofuel and carbon capture technologies(Wiley, 2016) N/A; Department of Industrial Engineering; Öztürk, Ali; Türkay, Metin; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956Environmental considerations has become a central issue in the process industries. The energy sector attracts the majority of attention, since it is responsible from 83% of anthropogenic greenhouse gas emissions. Although the renewable energy technologies are surging, fossil fuels are expected to continue dominating the sector for the next decades. Therefore, it is important to analyze the performance of emerging technologies that can be integrated into existing facilities, such as biofuels and carbon capture and storage (CCS) technologies. In this article, we present a multi-period bicriteria optimization model that represents traditional cogeneration processes and integrate biodiesel and CCS technologies. Then, the efficient set for the problem is obtained by using a novel two-phase solution method. The results show that the modeling approach is effective in identifying the set of efficient solutions for the integration strategies of biodiesel and CCS technologies.Publication Metadata only Classification of 1,4-dihydropyridine calcium channel antagonists using the hyperbox approach(Amer Chemical Soc, 2007) N/A; N/A; Department of Industrial Engineering; Kahraman, Pınar; Türkay, Metin; Master Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956The early prediction of activity-related characteristics of drug candidates is an important problem in drug design. Activity levels of drug candidates are classified as low or high depending on their IC50 values. Because the experimental determination of IC50 values for a vast number of molecules is both time-consuming and expensive, computational approaches are employed. In this work, we present a novel approach to classify the activities of drug molecules. We use the hyperbox classification method in combination with partial least-squares regression to determine the most relevant molecular descriptors of the drug molecules for an efficient classification. The effectiveness of the approach is illustrated on DHP derivatives. The results indicate that the proposed approach outperforms other approaches reported in the literature.Publication Metadata only Design of reverse logistics network for waste batteries with an application in Turkey(aidic Servizi Srl, 2013) N/A; Department of Industrial Engineering; Dönmez, İrem; Türkay, Metin; Master Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956the demand for portable electronic devices grows everyday and the batteries that power them pose important environmental problems. Batteries contain heavy metals such as; lead, mercury, cadmium that can contaminate the environment when batteries are disposed of improperly. the question is "How to manage this large amount of waste batteries?" in order to minimize the negative impacts of batteries on the environment, legislations have been published in the last two decades. in Turkey, the Regulation on Control of Waste Batteries and accumulators aPaK is published in 2004 and the project 'Development of Waste Battery Disposal and Recycling Technologies' is in progress. Within the scope of the project we do research on logistics of waste batteries. a multi period mixed-integer linear programming (MILP) model is developed to design the reverse logistics network for waste batteries. We solved the model with the objective of minimizing the total present value of waste battery management system under a variety of scenarios in order to provide an effective decision support tool and offer useful outputs to decision-makers.Publication Metadata only Energy network optimization in an oil refinery(Elsevier, 2018) Mete, Elif; Department of Industrial Engineering; Türkay, Metin; Faculty Member; Department of Industrial Engineering; College of Engineering; 24956Management of energy is a critical factor in refinery operations, having a significant impact on the production costs. The effective management of the energy system in the refinery can improve the economic performance significantly. The energy demand in refineries changes continuously in the presence of changing crude oil properties, operation conditions of process units, and cost of fuels. We present a decision support system to manage the complex energy network of the refinery by determining the optimum operational combinations of the equipment for minimizing the energy costs. In addition to operational optimization of the energy network, we also examine the impact of policy decisions through scenario analysis. We show that around 3.5 % cost reduction is possible without capital investment.Publication Metadata only Hybrid systems: modeling, simulation and optimization(Elsevier Sci Ltd, 2009) Karasözen, Bülent; Biegler, Lorenz T.; McAvoy, Thomas J.; Department of Industrial Engineering; Türkay, Metin; Faculty Member; Department of Industrial Engineering; College of Engineering; 24956N/APublication Metadata only Identification of novel small molecules targeting core clock proteins to regulate circadian rhythm(Elsevier Sci Ltd, 2022) Gul, Seref; Department of Chemical and Biological Engineering; Department of Industrial Engineering; Kavaklı, İbrahim Halil; Türkay, Metin; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Industrial Engineering; College of Engineering; College of Engineering; 40319; 24956The circadian rhythms are physiological, biochemical, and behavioral oscillations that cycle every 24 hours to anticipate the daily changes in the external environment. Disruption of the circadian clock in mammals results in increased susceptibility to different types of diseases such as metabolic, mood and sleep disorders and cancer. To this end, different approaches have been taken to find small molecules that have the potential to correct the disrupted circadian clock. In this review, we highlight the recent developments in identifying novel molecules that regulate the activities of the core clock proteins. Finally, we discuss virtual screening-based methods using the crystal structures of core clock proteins for the discovery of small molecules that regulate the circadian rhythm.Publication Metadata only Inferring transferable intermolecular potential models(2008) Üçyigitler, Sinan; Çamurdan, Mehmet C.; Elliott, J. Richard; Department of Industrial Engineering; Türkay, Metin; Faculty Member; Department of Industrial Engineering; College of Engineering; 24956Discontinuous molecular dynamics is combined with thermodynamic perturbation theory to provide an efficient basis for characterising molecular interactions based on vapour pressure and liquid density data. Several prospective potential models are discretised to permit treatment by Barker–Henderson perturbation theory. The potentials are characterised by 11 wells ranging over radial distances from the site diameter to three times that diameter. Considered potential models include the Lennard-Jones (LJ), square-well, Yukawa (Yuk) and multi-line potentials, and their combinations. The optimal model is found to be a combination of square-well and Yuk potentials, with the switch position and Yuk decay set to universal values. This model provides average vapour pressure deviations of less than 10% for a database of 86 aliphatic, aromatic and naphthenic compounds. The LJ potential provides the least competitive accuracy. Considering statistical information criteria facilitates the identification of the optimal model.Publication Metadata only Multi-company collaborative supply chain management with economical and environmental considerations(Elsevier, 2004) Fujita, K; Asakura, T; Department of Industrial Engineering; N/A; Türkay, Metin; Oruç, Cihan; Faculty Member; Master Student; Department of Industrial Engineering; College of Engineering; Graduate School of Sciences and Engineering; 24956; N/AProcess systems must interact with other systems for a better production performance. The interaction among process systems is usually established when these systems exchange materials such as steam and electricity. Integrated analysis of different process systems can provide valuable insight and also identify improvements in the financial and environmental performance of industrial supply chain systems. A systematic approach to identify the synergy among different process systems has been developed. The proposed approach uses three steps; the generation of standardized models for process units, integration of process unit models for the supply chain system and solution of the model and analysis of the results. The developed approach is illustrated with an example that is a simplified version of a real problem and tested on an industrial problem. It is shown that important improvements in the cost and release of environmentally harmful emissions can be accomplished by integration of different process systems.Publication Metadata only Multiobjective optimization of mixed-integer linear programming problems: a multiparametric optimization approach(Amer Chemical Soc, 2021) Pappas, Iosif; Avraamidou, Styliani; Katz, Justin; Burnak, Barış; Beykal, Burcu; Pistikopoulos, Efstratios N.; Department of Industrial Engineering; Türkay, Metin; Faculty Member; Department of Industrial Engineering; College of Engineering; 24956Industrial process systems need to be optimized, simultaneously satisfying financial, quality, and safety criteria. To meet all of those potentially conflicting optimization objectives, multiobjective optimization formulations can be used to derive optimal trade-off solutions. In this work, we present a framework that provides the exact Pareto front of multiobjective mixed- integer linear optimization problems through multiparametric programming. The original multiobjective optimization program is reformulated through the well-established c-constraint scalarization method, in which the vector of scalarization parameters is treated as a right-hand side uncertainty for the multiparametric program. The algorithmic procedure then derives the optimal solution of the resulting multiparametric mixed-integer linear programming problem as an affine function of the. parameters, which explicitly generates the Pareto front of the multiobjective problem. The solution of a numerical example is analytically presented to exhibit the steps of the approach, while its practicality is shown through a simultaneous process and product design problem case study. Finally, the computational performance is benchmarked with case studies of varying dimensionality with respect to the number of objective functions and decision variables.