Mühendislik Fakültesi / Faculty of Engineering

Permanent URI for this collectionhttps://hdl.handle.net/11727/1401

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Author: search.filters.author.Dengiz, Bernasearch.filters.applied.f.rights: search.filters.rights.info:eu-repo/semantics/openAccess

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Now showing 1 - 8 of 8
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    The Efficiency of Variance Reduction in Manufacturing and Service Systems: The Comparison of the Control Variates and Stratified Sampling
    (2009) Eraslan, Erguen; Dengiz, Berna; 0000-0002-5667-0391; AAE-7165-2019
    There has been a great interest in the use of variance reduction techniques (VRTs) in simulation output analysis for the purpose of improving accuracy when the performance measurements of complex production and service systems are estimated. Therefore, a simulation output analysis to improve the accuracy and reliability of the output is required. The performance measurements are required to have a narrow and strong confidence interval. For a given confidence level, a smaller confidence interval is supposed to be better than the larger one. The wide of confidence interval, determined by the half length, will depend on the variance. Generally, increased replication of the simulation model appears to have been the easiest way to reduce variance but this increases the simulation costs in complex-structured and large-sized manufacturing and service systems. Thus, VRTs are used in experiments to avoid computational cost of decision-making processes for more precise results. In this study, the effect of Control Variates (CVs) and Stratified Sampling (SS) techniques in reducing variance of the performance measurements of M/M/1 and GI/G/1 queue models is investigated considering four probability distributions utilizing randomly generated parameters for arrival and service processes. Copyright (C) 2009 E. Eraslan and B. Dengiz.
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    Fractional Universal Kriging Metamodel
    (2022) Balaban, Muzaffer; Dengiz, Berna
    In this study, a Kriging-based metamodel is proposed that can be used instead of the simulation model for complex problems where data generation with a simulation model may be costly. In this new model structure, which is proposed for cases where the drift function structure of the Universal Kriging meta-model is not known. A power function of the variables that can also take fractional values is used instead of the first and second order regression models used as the drift function in the Universal Kriging metamodel. The predictive power of this metamodel, which is called Fractional Universal Kriging metamodel, has been investigated by experimentally computational analysis. Validation analysis reveals that the Fractional Universal Kriging metamodels have superior predictive power with respect to Mean Squared Error and Maximum Squared Error performance measures. Thus, in the case that the input-output relationship of the simulation model can be expressed with a power function that includes the effects of higher order and different from the quadratic polynomial case, Fractional Universal Kriging metamodels are proposed as a new metamodel approach.
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    A Local Search Heuristic with Self-tuning Parameter for Permutation Flow-Shop Scheduling Problem
    (2009) Dengiz, Berna; Alabas-Uslu, Cigdem; Sabuncuoglu, Ihsan
    In this paper, a new local search metaheuristic is proposed for the permutation flow-shop scheduling problem. In general, metaheuristics are widely used to solve this problem due to its NP-completeness. Although these heuristics are quite effective to solve the problem, they suffer from the need to optimize parameters. The proposed heuristic, named STLS, has a single self-tuning parameter which is calculated and updated dynamically based on both the response surface information of the problem field and the performance measure of the method throughout the search process. Especially, application simplicity of the algorithm is attractive for the users. Results of the experimental study show that STLS generates high quality solutions and outperforms the basic tabu search, simulated annealing, and record-to-record travel algorithms which are well-known local search based metaheuristics.
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    A New Multi-Echelon Repair Network Model with Multiple Upstream Locations for Level of Repair Analysis Problem
    (2021) Bicakci, Ismail; Ic, Yusuf Tansel; Karasakal, Esra; Dengiz, Berna; 0000-0001-9274-7467; AGE-3003-2022
    Level of repair analysis (LORA) determines (1) the best decision during a malfunction of each product component; (2) the location in the repair network to perform the decision and (3) the quantity of required resources in each facility. Capital goods have long life cycles and their total life cycle costs are extremely high. LORA, which can be done repeatedly during the life cycle of the product, both at design and product support phase, plays an important role in minimising the total life cycle costs of capital goods. It is mostly applied to systems that operate in different geographical areas and deployed in different regions, which include different subsystems with special technology and expertise, and have a complex product structure. In this study, we propose a new mathematical model to the LORA problem, which is more comprehensive and flexible than the other pure LORA models in the literature. The proposed model uses the multiple upstream approach that allows the transfer of the components from a location in the lower echelon to the predefined locations in the upper echelon and determines the material movement paths between each facility, defining the facilities' locations in the repair network. The performance of the proposed model is tested on benchmark instances and the results are compared with the single upstream model. Computational experiments show that the proposed model is more effective than the single upstream model and reduces the total life cycle costs by 4.85% on average, which is an enormous cost saving when total life cycle costs of capital goods are considered.
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    Modified self-adaptive local search algorithm for a biobjective permutation flow shop scheduling problem
    (2019) Alabas Uslu, Cigdem; Dengiz, Berna; Aglan, Canan; Sabuncuoglu, Ihsan
    Interest in multiobjective permutation flow shop scheduling (PFSS) has increased in the last decade to ensure effective resource utilization. This study presents a modified self-adaptive local search (MSALS) algorithm for the biobjective permutation flow shop scheduling problem where both makespan and total flow time objectives are minimized. Compared to existing sophisticated heuristic algorithms, MSALS is quite simple to apply to different biobjective PFSS instances without requiring effort or time for parameter tuning. Computational experiments showed that MSALS is either superior to current heuristics for Pareto sets or is incomparable due to other performance indicators of multiobjective problems.
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    An integrated simulation model for analysing electricity and gas systems
    (2014) Erdener, Burcin Cakir; Pambour, Kwabena A.; Lavin, Ricardo Bolado; Dengiz, Berna
    This paper aims at analysing the impacts of interdependencies between electricity and natural gas systems in terms of security of energy supply. When analysing both systems several interdependencies can be observed, however, the most significant interdependencies are as follows: (1) gas dependency of gas fired power plants in electricity system and (2) electric dependency of electric-driven compressors in gas system. Since both systems depend on each other, it is of major interest from an energy security perspective to investigate how failures triggered in either of the systems propagate from one system to the other. We proposed an integrated simulation model that aims at reflecting the dynamics of the systems in case of disruptions and takes the cascading effects of these disruptions into account. While developing the integrated model, first electricity and gas systems are modelled separately and then linked by an (MATLAB-based) interface. The effectiveness of the proposed model is investigated using characteristic disruption scenarios. Computational results demonstrate that the integrated simulation model is very user-friendly and quite effective and efficient in analysing the interactions between electricity and gas systems. (C) 2014 The Authors. Published by Elsevier Ltd.
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    WEEE estimation and determination of collection points: A case for the Municipality of Cankaya
    (2018) Kececi, Baris; Dengiz, Orhan; Dengiz, Berna; Sumer, Emre; Kilic, Aybuke; Ceki, Ece; Inan, Bedia; Cicek, Selda; 0000-0002-2730-5993; F-1639-2011; AAC-4793-2019
    Electrical-electronic waste (WEEE) is generated from electric and electronic devices at the end of their lifecycles. When WEEEs are disposed, burned or disassembled for recycling, they are transformed into products containing hazardous substances and harm the environment and human health. Therefore WEEEs should be collected, transported and processed properly during their recycling operations by municipality authority in order to minimize their damage and maximize their economic benefit. In this paper, a study is carried out for the WEEE management of Cankaya Municipality by the cooperation of Environmental Conservation and Control Department of Cankaya. For this purpose first WEEE with a focus on television, refrigerator, washing machine, oven and vacuum cleaner are estimated based on the electronic device usage behavior of residents in Cankaya. Secondly, the WEEE collection points' location problem is solved considering set covering problem.