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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, WilcoWe 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, İpekIn 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 DBN based reactive maintenance model for a complex system in thermal power plants(Elsevier Sci Ltd, 2019-10) Özgür Ünlüakın, Demet; Türkali, Busenur; Karacaörenli, Ayşe; Aksezer, Sezgin ÇağlarThermal power plants consist of several complex systems having many interacting hidden components. Any unexpected failure may lead to prolonged downtime and serious lost profits. Therefore, implementing an effective maintenance policy is crucial for this sector. Although preventive maintenance has become a more popular strategy, it does not completely prevent the need for corrective maintenance. Our aim in this study is to tackle the corrective maintenance implementation problem of a multi-component partially observable dynamic system based on a regenerative air heater in a thermal power plant. We propose eight methods having different efficiency measures with respect to time, effect and probability criteria to minimize the total number of maintenance activities in a given planning horizon. Performances of these methods are evaluated under corrective maintenance strategy using dynamic Bayesian networks. The results show that fault effect methods with best working state probability measure perform better than the others considering both the total amount of maintenance activities and also the solution time. We also point out how the methods can be implemented in real-life and how the results can be used for requirements planning. Furthermore, the proposed methods can be used for the corrective maintenance of all systems having hidden interacting components.Yayın A mathematical model for perishable products with price- and displayed-stock-dependent demand(Elsevier Ltd, 2016-12) Önal, Mehmet; Yenipazarlı, Arda; Kundakçıoğlu, Ömer ErhunWe 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, YamanSensitivity 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 Tractable supply chain production planning, modeling nonlinear lead time and quality of service constraints(Elsevier Ltd, 2007) Anlı, Osman Murat; Caramanis, Michael C.; Paschalidis, Ioannis Ch.This paper addresses the task of coordinated planning of a supply chain (SC). Work in process (WIP) in each facility participating in the SC, finished goods inventory, and backlogged demand costs are minimized over the planning horizon. In addition to the usual modeling of linear material flow balance equations, variable lead time (LT) requirements, resulting from the increasing incremental WIP as a facility's utilization increases, are also modeled. In recognition of the emerging significance of quality of service (QoS), that is control of stockout probability to meet demand on time, maximum stockout probability constraints are also modeled explicitly. Lead time and QoS modeling require incorporation of nonlinear constraints in the production planning optimization process. The quantification of these nonlinear constraints must capture statistics of the stochastic behaviour of production facilities revealed during a time scale for shorter than the customary weekly time scale of the planning process. The apparent computational complexity of planning production against variable LT and QoS constraints has long resulted in MRP-based scheduling practices that ignore the LT and QoS constraints has long resulted in MRP-based scheduling practices that ignore the LT and QoS impact to the plan's detriment. The computational complexity challenge was overcome by proposing and adopting a time-scale decomposition approach to production planning where short-time-scale stochastic dynamics are modeled in multiple facility-specific subproblems that receive tentative targets from a deterministic master problem and return statistics to it. A converging and scalable iterative methodology is implemented, providing evidence that significantly lower cost production plans are achievable in a computationally tractable manner.Yayın Cost-effective fault diagnosis of a multi-component dynamic system under corrective maintenance(Elsevier Ltd, 2021-04) Özgür Ünlüakın, Demet; Türkali, Busenur; Aksezer, Sezgin ÇağlarMaintenance planning and execution are challenging tasks for every system with complex structure. Interdependent nature of the components that builds up the system may have significant effect on system integrity. While preventive maintenance actions can be carried out in a more planned fashion, corrective actions are more time sensitive as they directly affect the availability of the system. This study proposes a cost-effective dynamic Bayesian network modeling scheme to be used in the planning of corrective maintenance actions on systems having hidden components which have stochastic and structural dependencies. In such context, the regenerative air heater system which is a key element of a power plant is taken into consideration. The proposed maintenance framework offers several methods, each aiming to balance the cost with the probability effect using a normalization procedure. The methodologies are extensively simulated for sensitivity analysis under various downtime cost values. Fault effect methods with worst state probability efficiency measures give the least total cost for all downtime cost values and their distinction becomes significant as this value increases. Further statistical analysis concludes that considerable gains on maintenance costs can be achieved by the proposed approach.Yayın Maintenance policy analysis of the regenerative air heater system using factored POMDPs(Elsevier Ltd, 2022-03) Kıvanç, İpek; Özgür Ünlüakın, Demet; Bilgiç, TanerMaintenance optimization of multi-component systems is a difficult problem. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for such problems under uncertainty in stochastic environments. In this study, the main POMDP solution approaches and solvers are surveyed. Then, based on experimental models with different complexities in the size of the system space, selected POMDP solvers using different representation patterns for modeling and different procedures for updating the value function while solving are compared. Furthermore, to show that factored representations are advantageous in modeling and solving the maintenance problem of multi-component systems where there exist also stochastic dependencies among the components, the maintenance problem of the one-line regenerative air heater system available in thermal power plants is modeled and solved with factored POMDPs. In-depth sensitivity analyses are performed on the obtained policy. The results show that factored POMDPs enable compact modeling, efficient policy generation and practical policy analysis for the tackled problem. Furthermore, they also motivate the use of factored POMDPs in the generation and analysis of maintenance policies for similar multi-component systems.Yayın Failure analysis and warranty modeling of used cars(Pergamon-Elsevier Science Ltd, 2011-09) Aksezer, Sezgin ÇağlarReliability is an important aspect of product perception and manufacturers are compelled to take corrective actions on the items failing within the warranty period. Automotive manufacturers are being exposed to significant operating costs as a result of warranty claims affecting an individual unit or mandatory (sometimes voluntary) recalls affecting a batch. Underlying principles of warranty modeling are built by considering both subjective issues and objective constraints such as competition, quality, and performance under the goal of achieving desired levels of reliability and cost in a balanced manner. This paper reviews the warranty cost models with an emphasis on the failure analysis of used vehicles. Expected warranty costs are calculated by taking into account the age, usage, and maintenance data of the product in question. Failure intensities and characteristics are identified in order to propose a policy that highlights the trade-off between the cost and the warranty length. A case study on a popular brand's initiation of factory certified pre-owned program for the local automobile market of Turkey is presented in detail. (C) 2011 Elsevier Ltd. All rights reserved.Yayın Reliability evaluation of healthcare services by assessing the technical efficiency(Routledge Journals, Taylor & Francis Ltd, 2011) Aksezer, Sezgin ÇağlarClassical 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.
