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Listeleniyor 1 - 10 / 13
  • Yayın
    The economic lot-sizing problem with perishable items and consumption order preference
    (Elsevier Science BV, 2015-08-01) Önal, Mehmet; Romeijn, H. Edwin; Sapra, Amar; Van den Heuvel, Wilco
    We consider the economic lot-sizing problem with perishable items (ELS-PI), where each item has a deterministic expiration date. Although all items in stock are equivalent regardless of procurement or expiration date, we allow for an allocation mechanism that defines an order in which the items are allocated to the consumers. In particular, we consider the following allocation mechanisms: First Expiration, First Out (FEFO), Last Expiration, First Out (LEFO), First In, First Out (FIFO) and Last In, First Out (LIFO). We show that the ELS-PI can be solved in polynomial time under all four allocation mechanisms in case of no procurement capacities. This result still holds in case of time-invariant procurement capacities under the FIFO and LEFO allocation mechanisms, but the problem becomes NP-hard under the FEFO and LIFO allocation mechanisms.
  • Yayın
    Assortment optimization with log-linear demand: application at a Turkish grocery store
    (Elsevier Ltd, 2019-09) Hekimoğlu, Mustafa; Sevim, İsmail; Aksezer, Sezgin Çağlar; Durmuş, İpek
    In retail sector, product variety increases faster than shelf spaces of retail stores where goods are presented to consumers. Hence, assortment planning is an important task for sustained financial success of a retailer in a competitive business environment. In this study, we consider the assortment planning problem of a retailer in Turkey. Using empirical point-of-sale data, a demand model is developed and utilized in the optimization model. Due to nonlinear nature of the model and integrality constraint, we find that it is difficult to obtain a solution even for moderately large product sets. We propose a greedy heuristic approach that generates better results than the mixed integer nonlinear programming in a reasonably shorter period of time for medium and large problem sizes. We also proved that our method has a worst-case time complexity of O(n 2 )while other two well-known heuristics’ complexities are O(n 3 )and O(n 4 ). Also numerical experiments reveal that our method has a better performance than the worst-case as it generates better results in a much shorter run-times compared to other methods.
  • Yayın
    A mathematical model for perishable products with price- and displayed-stock-dependent demand
    (Elsevier Ltd, 2016-12) Önal, Mehmet; Yenipazarlı, Arda; Kundakçıoğlu, Ömer Erhun
    We introduce an economic order quantity model that incorporates product assortment, pricing and space-allocation decisions for a group of perishable products. The goal is to maximize the retailer's profit under shelf-space and backroom storage capacity constraints. We assume that the demand rate of a product is a function of the selling prices and the displayed stock levels of all the products in the assortment. We propose a Tabu Search based heuristic method to solve this complex problem.
  • Yayın
    Sensitivity analysis for models with multiple behavior modes: a method based on behavior pattern measures
    (2016-12) Hekimoğlu, Mustafa; Barlas, Yaman
    Sensitivity analysis of system dynamics models is essentially about sensitivity of patterns of output behaviors to inputs, since system dynamics modeling is behavior pattern oriented. In this study, a regression-based procedure for pattern sensitivity analysis is developed, by defining behavior pattern measures such as equilibrium level, trend, inflection point, or oscillation amplitude. A unique feature of the procedure is that it takes into account the possibility of a model generating multiple behavior modes. This pattern-oriented procedure is next applied to the tipping point project management model and a generic supply line model. These test applications yield sensitivity results that are meaningful, and also consistent with previously available sensitivity information about the parameters of these models. Finally, our pattern sensitivity analysis is shown to be a useful and effective method also for oscillatory system dynamics models, an unsolved sensitivity problem previously in the literature.
  • Yayın
    A stochastic risk-averse framework for blood donation appointment scheduling under uncertain donor arrivals
    (Springer, 2020-12) Yalçındağ, Semih; Baş Güre, Seda; Carello, Giuliana; Lanzarone, Ettore
    Blood is a key resource in all health care systems, usually drawn from voluntary donors. We focus on the operations management in blood collection centers, which is a key step to guarantee an adequate blood supply and a good quality of service to donors, by addressing the so-called Blood Donation Appointment Scheduling problem. Its goal is to employ appointment scheduling to balance the production of blood units between days, in order to provide a reasonably constant supply to transfusion centers and hospitals, and reduce non-alignments between physicians' working times and donor arrivals at the collection center. We consider a two-phase solution framework taken from the literature, in which a deterministic linear programming model preallocates time slots to different blood types and a prioritization policy assigns the preallocated slots to the donors when they make a reservation. However, the problem is stochastic in nature and requires consideration of the uncertain arrivals of non-booked donors. In this work, to include the uncertain arrivals, we propose three stochastic counterparts of the preallocation model based on a risk-neutral objective and two risk-averse objectives, respectively, where the Conditional Value-at-Risk is considered as the risk measure in the last two methods. The resulting stochastic frameworks have been tested considering the historical data of one of the largest Italian collection centers, the Milan Department of the "Associazione Volontari Italiani Sangue" (AVIS). Results show the effectiveness of the stochastic models, especially the mean-risk one, and the need to include the uncertainty of arrivals in order to better balance the production of blood units.
  • Yayın
    Challenges in the CO2 emissions of the Turkish power sector: Evidence from a two-level decomposition approach
    (Elsevier Ltd, 2021-06) Işık, Mine; Ari, İzzet; Sarıca, Kemal
    Decarbonization of the energy system is urgent to avert the disruptions in the climate. Considering its share, the low carbon transition of the power sector is pivotal. Growing electricity demand poses unique challenges for Turkey to enact deep decarbonization. It is vital to uncover the contributing causes of emissions to provide strategic oversight for carbon management activities. This study investigates key drivers of CO2 emissions from the power sector using the Logarithmic Mean Divisia Index decomposition method. While efficiency improvement contributes to sustainable yet minor mitigation, changes in the fossil-fuel share indicate a cycling but significant overall impact.
  • Yayın
    Economic impacts of increased U.S. exports of natural gas: An energy system perspective
    (MDPI AG, 2016-05-25) Sarıca, Kemal; Tyner, Wallace E.
    With the recent shale gas boom, the U.S. is expected to have very large natural gas resources. In this respect, the key question is would it be better to rely completely on free market resource allocations which would lead to large exports of natural gas or to limit natural gas exports so that more could be used in the U.S.. After accounting for the cost of liquefying the natural gas and shipping it to foreign markets, the current price difference leaves room for considerable profit to producers from exports. In addition, there is a large domestic demand for natural gas from various sectors such as electricity generation, industrial applications, and the transportation sector etc. A hybrid modeling approach has been carried out using our version of the well-known MARket ALlocation (MARKAL)-Macro model to keep bottom-up model richness with macro effects to incorporate price and gross domestic product (GDP) feedbacks. One of the conclusion of this study is that permitting higher natural gas export levels leads to a small reduction in GDP (0.04%-0.17%). Higher exports also increases U.S. greenhouse gas (GHG) emissions and electricity prices (1.1%-7.2%). We also evaluate the impacts of natural gas exports in the presence of a Clean Energy Standard (CES) for electricity. In this case, the GDP impacts are similar, but the electricity and transport sector impacts are different.
  • Yayın
    Reliability evaluation of healthcare services by assessing the technical efficiency
    (Routledge Journals, Taylor & Francis Ltd, 2011) Aksezer, Sezgin Çağlar
    Classical reliability analysis techniques of manufacturing and defence industries are not a perfect fit for the assessment of the reliability of services. This is partly due to the lack of proper and valid reliability testing procedures in service systems and complications faced in identifying critical service parameters. Since most prominent performance indicators of a system can be associated with the maximum overall reliability it achieves, then factors that degrade the reliability can be identified with respect to its superior peers. This study utilizes the data envelopment analysis for the evaluation of reliability in service systems with a focus on healthcare. This approach comparably evaluates the performance of a service provider over a period of time by means of failure rates and identifies the factors affecting unreliable time phases. Application of the proposed method is illustrated with a private Turkish hospital along with an example of failure mode and effect analysis for inpatient treatment.
  • Yayın
    Simultaneous scheduling of football games and referees using Turkish league data
    (Blackwell Publishing Ltd, 2017-05) Atan, Sabri Tankut; Hüseyinoğlu, Olgu Pelin
    Assignment decisions of referees to football (soccer) games are highly debated in sports media. Referee assignments are typically done on a weekly basis as the league progresses. However, this practice ignores important workload constraints on referees. Moreover, referees' skill levels should also be considered in determining their assignments. In this article, we first give a mixed integer linear program formulation for the problem of simultaneously generating a game schedule and assigning main referees to games by incorporating specific rules in the Turkish league. We also approach this problem using a genetic algorithm (GA) because of the computational difficulties in solving the problem. In the GA solution pool, we suggest using templates for referee assignments that follow several referee-related workload constraints. We explain how these templates can be obtained by solving a mixed integer linear model prior to running the GA. The usage of these templates for referee assignments is conceptually similar to using a basic match schedule for game scheduling such as the one used in the Turkish Football League. We use the Turkish Football League fixtures for 2010–2013 as a case study. Experiments with the GA using real-world data show a rather modest performance in terms of computation time and objective function value. Our numerical results indicate that the problem is extremely hard to solve.
  • Yayın
    Investment in improved inventory accuracy in a decentralized supply chain
    (Elsevier Science BV, 2008-06) Uçkun, Canan; Karaesmen, Ahmet Fikri; Savaş, Selçuk
    It is known that inaccurate inventory records can lead to profit losses in a supply chain. Inventory records may not be correct due to various reasons such as transaction errors, misplacement, shrinkage, etc. In order to eliminate inventory inaccuracy, companies may invest in new information technologies such as radio frequency identification (RFID). In this paper, we consider a supply chain consisting of a retailer (distributor) and a supplier. We assume a single-period newsvendor-type setting where the retailer purchases the items from the supplier and distributes them to the regional warehouses. The paper focuses on the problem of finding the optimal investment levels that maximize profit by decreasing inventory inaccuracy. The optimal level of investment is examined both for the centralized and the decentralized systems under two scenarios: inventory sharing between the warehouses is allowed and not allowed. The coordination problem is also considered for both scenarios. Finally, several extensions of the model are considered: asymmetric warehouse parameters, demand and inventory inaccuracy correlation and imperfect RFID implementation.