Scholarly Publications - Industrial Engineering

Permanent URI for this collectionhttps://hdl.handle.net/11693/115612

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Open Access
Technical note—optimal procurement in remanufacturing systems with uncertain used-item condition
(INFORMS Inst.for Operations Res.and the Management Sciences, 2023-05-08) Nadar, Emre; Akan, Mustafa; Debo, Laurens; Scheller-Wolf, Alan
We consider a single-product remanufacture-to-order system with multiple uncertain quality levels for used items, random procurement lead times, and lost sales. The quality level of a used item is revealed only after it is acquired and inspected; the remanufacturing cost is lower for a higher-quality item. We model this system as a Markov decision process and seek an optimal policy that specifies when a used item should be procured, whether an arriving demand for the remanufactured product should be satisfied, and which available item should be remanufactured to meet this demand. We characterize the optimal procurement policy as following a new type of strategy: state-dependent noncongestive acquisition. This strategy makes decisions, taking into account the system congestion level measured as the number of available items and their quality levels. We also show that it is always optimal to meet the demand with the highest-quality item among the available ones. We conclude with extensions of our model to limited cases when the used-item condition is known a priori (for two quality levels) and remanufacture-to-stock systems in which the standard push strategy is optimal in the remanufacturing stage. © 2023 INFORMS.
Open Access
Discovering sustainability practices in research and innovation sites
(ARROW@TU, 2023-10-10) Downey, Robin Ann
Discovering sustainability pr ering sustainability practices in resear actices in research and inno ch and innovation This practice paper is a descriptive account of an experience with a sustainable development learning project for engineering students in a Science, Technology and Society (STS) course at Bilkent University. The students participated in the STS Sustainability Awards competition for two semesters in one academic year, an event that was inspired by Bilkent University’s 2021–2022 Sustainability Year. As part of the project, the students found a company or laboratory, consulted them on their innovation practices and asked questions that were grounded in Responsible Research and Innovation (RRI) approaches. RRI can provide an opening for students to explore how various values, including sustainability and privacy, are considered in innovation practices. The values by design approach can help engineering students to see that innovators consider both instrumental and qualitative values during the innovation process. Although the project has been used in other years, the sustainability awards motivated students to explore how innovators respond to concerns around a range of sustainability issues. The award recipients produced projects on smart homes, nanotechnology-based solar panels, clean meat, industry 4.0, geothermal energy, air cars and magnetic resonance imaging technology, and gave presentations in events hosted by the Faculty of Engineering administrators. Although future research in this area is needed, applied learning experiences, such as the one that is described in this paper, could have the potential to help bridge the disciplinary divide between STS and engineering.
Open Access
Student perspectives on sustainability in engineering education: multiple case study of european bachelor's programs in industrial engineering and management
(ARROW@TU, 2023-10-10) Trigueiros, Francisca; Kaipainen, Jenni; Silva, Frederico; Geising, Niklas; Tosun, Erdem Ata
The global sustainability crisis is calling for engineers to take action. To enable and empower engineers to address this crisis, there must be a change in engineering education. Given the industry's key role in not only causing but also solving this sustainability crisis, it is especially crucial to improve how sustainability is addressed in industrial engineering and management (IEM) education. This paper examines (1) to which extent European IEM degrees are covering sustainability; (2) European IEM students’ motivations to learn and work with sustainability topics; and (3) their perceptions of their degree’s contribution to their knowledge and motivation regarding sustainability; and (4) which sustainability-related changes they would like to see in their degrees. Three IEM curricula covering different regions of Europe—Portugal, Germany, and Turkey—were analysed. The mixed-method analysis included a quantitative evaluation of the extent to which each course meets specific theory-based learning objectives pertinent to sustainability in engineering education. The analysis was complemented by students’ perspectives, which were gathered through group discussions and interviews. The results reveal how sustainability is addressed in IEM education in different European regions, its impact on students’ knowledge and motivation for sustainability issues, and how sustainability in engineering education should be developed based on students' perceptions. These findings contribute to the research on sustainability in engineering education and support university teachers in revising engineering study programs to provide adequate sustainability understanding and skills to students.
Embargo
Word of mouth on action: analysis of optimal shipment policy when customers are resentful
(Elsevier Ltd, 2023-03-04) Çavdar, Bahar; Erkip, Nesim Kohen
Word-of-Mouth (WoM) communication via online reviews plays a vital role in customers’ purchasing decisions. As such, retailers must consider the impact of WoM to manage customer perceptions and future demand. This paper considers an online shopping system with premium and regular customers. Building on the behavioral and operations management literature, we model customer preferences based on the perceived service quality indicated by WoM and integrate this into the retailer's operational problem to determine a shipment policy regarding the timing of consolidated shipments and the treatment of regular demand. First, we study the e-tailer's problem when they have no knowledge of WoM and only react to the changes in demand. We analyze the long-term behavior of customer demand and show that potential market size and customer sensitivity are the key parameters determining this behavior. Then, we build a model to integrate the knowledge of WoM into operational decision-making and partially characterize the optimal solution. We show that (i) underpromise-and-overdeliver can be a hurtful strategy since it creates a false sense of fast delivery for the regular service, (ii) relaxations in operational constraints may hurt profitability due to the associated difficulties of managing perceptions, and (iii) seeking a stationary policy can lead to suboptimal solutions; therefore, cyclic policies should also be considered when appropriate. © 2023
Open Access
Outer approximation algorithms for convex vector optimization problems
(Taylor and Francis Ltd., 2023-02-09) Keskin, İrem Nur; Ulus, Firdevs
In this study, we present a general framework of outer approximation algorithms to solve convex vector optimization problems, in which the Pascoletti-Serafini (PS) scalarization is solved iteratively. This scalarization finds the minimum ‘distance’ from a reference point, which is usually taken as a vertex of the current outer approximation, to the upper image through a given direction. We propose efficient methods to select the parameters (the reference point and direction vector) of the PS scalarization and analyse the effects of these on the overall performance of the algorithm. Different from the existing vertex selection rules from the literature, the proposed methods do not require solving additional single-objective optimization problems. Using some test problems, we conduct an extensive computational study where three different measures are set as the stopping criteria: the approximation error, the runtime, and the cardinality of the solution set. We observe that the proposed variants have satisfactory results, especially in terms of runtime compared to the existing variants from the literature. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
Open Access
Computation of systemic risk measures: a mixed-integer programming approach
(INFORMS Inst.for Operations Res.and the Management Sciences, 2023-09-22) Ararat, Çaǧın; Meimanjan, N.
Systemic risk is concerned with the instability of a financial system whose members are interdependent in the sense that the failure of a few institutions may trigger a chain of defaults throughout the system. Recently, several systemic risk measures have been proposed in the literature that are used to determine capital requirements for the members subject to joint risk considerations. We address the problem of computing systemic risk measures for systems with sophisticated clearing mechanisms. In particular, we consider an extension of the Rogers-Veraart network model where the operating cash flows are unrestricted in sign. We propose a mixed-integer programming problem that can be used to compute clearing vectors in this model. Because of the binary variables in this problem, the corresponding (set-valued) systemic risk measure fails to have convex values in general. We associate nonconvex vector optimization problems with the systemic risk measure and provide theoretical results related to the weighted-sum and Pascoletti-Serafini scalarizations of this problem. Finally, we test the proposed formulations on computational examples and perform sensitivity analyses with respect to some model-specific and structural parameters. Copyright: © 2023 INFORMS.
Open Access
A stochastic programming approach to surgery scheduling under parallel processing principle
(Elsevier Ltd, 2023-11-06) Çelik, Batuhan; Gül, Serhat; Çelik, Melih
Parallel processing is a principle which enables simultaneous implementation of anesthesia induction and operating room (OR) turnover with the aim of improving OR utilization. In this article, we study the problem of scheduling surgeries for multiple ORs and induction rooms (IR) that function based on the parallel processing principle under uncertainty. We propose a two-stage stochastic mixed-integer programming model considering the uncertainty in induction, surgery and turnover durations. We sequence patients and set appointment times for surgeries in the first stage and assign patients to IRs at the second stage of the model. We show that an optimal myopic policy can be used for IR assignment decisions due to the special structure of the model. We minimize the expected total cost of patient waiting time, OR idle time and IR idle time in the objective function. We enhance the model formulation using bounds on variables and symmetry-breaking constraints. We implement a novel progressive hedging algorithm by proposing a penalty update method and a variable fixing mechanism. Based on real data of a large academic hospital, we compare our solution approach with several scheduling heuristics from the literature. We assess the additional benefits and costs associated with the implementation of parallel processing using near-optimal schedules. We examine how the benefits are inflated by increasing the number of IRs. Finally, we estimate the value of stochastic solution to underline the importance of considering uncertainty in durations. © 2022 Elsevier Ltd
Open Access
Random sets and choquet-type representations
(American Institute of Mathematical Sciences, 2023-03) Ararat, Çağın; Çetin, U.
As appropriate generalizations of convex combinations with un-countably many terms, we introduce the so-called Choquet combinations, Cho-quet decomposable combinations and Choquet convex decomposable combinations, as well as their corresponding hull operators acting on the power sets of Lebesgue-Bochner spaces. We show that Choquet hull coincides with convex hull in the finite-dimensional setting, yet Choquet hull tends to be larger in infinite dimensions. We also provide a quantitative characterization of Cho-quet hull, without any topological or algebraic assumptions on the underlying set. Furthermore, we show that the Choquet decomposable hull of a set coincides with its strongly closed decomposable hull and the Choquet convex decomposable hull of a set coincides with the Choquet decomposable hull of its convex hull. It turns out that the measurable selections of a closed-valued multifunction form a Choquet decomposable set and those of a closed convex-valued multifunction form a Choquet convex decomposable set. Finally, we investigate the operator-type features of Choquet decomposable and Choquet convex decomposable hull operators when applied in succession. © 2023, American Institute of Mathematical Sciences. All rights reserved.
Open Access
Using micro-milled surface topography and force measurements to identify tool runout and mechanistic model coefficients
(Springer UK, 2023-02-15) Masrani, Abdulrzak; Karpat, Yiğit
Modeling the forces during micro-milling processes is directly linked to the chip load and mechanistic model parameters that are generally dependent on the tool/work combination. Tool runout, deflection, and the material’s elastic recovery mainly affect the chip load as a function of feed. Experimentally measured micro-milling forces can be employed to identify cutting force coefficients and runout parameters. However, decoupling the interplay among runout, deflection, and elastic recovery is difficult when only measured forces are considered. In this paper, machined surface topography has been considered as an additional process output to investigate the influence of runout and deflection separately. The machined surface topography was investigated using a scanning laser microscope to identify minimum chip thicknesss and runout parameters. A finite element model of tool deflection has been developed based on the end mill geometry used in the experiments. The finite element model was used to obtain a surrogate model of the tool deflection which was implemented into the mechanistic model. Nanoindentation tests were conducted on the coated WC tool to identify its material properties which are employed in the finite element model. An uncut chip thickness model is constructed by considering preceding trochoidal trajectories of the cutting edge, helix lag, tool runout, tool deflection, and the chip thickness accumulation phenomenon. The force model was validated experimentally by conducting both slot and side milling tests on commercially pure titanium (cp-Ti). The predicted cutting forces were shown to be in good agreement with the experimental cutting forces.
Embargo
Exact solution approaches for the minimum total cost traveling salesman problem with multiple drones
(Elsevier, 2023-01-04) Özbaygın Tiniç, G.; Karasan, Oya Ekin; Kara, Bahar Yetiş; Campbell, J.F.; Özel. A.
Deployment of drones in delivery operations has been attracting growing interest from the commercial sector due to its prospective advantages for a range of distribution systems. Motivated by the widespread adoption of drones in last-mile delivery, we introduce the minimum cost traveling salesman problem with multiple drones, where a truck and multiple drones work in synchronization to deliver parcels to customers. In this problem, we aim to find an optimal delivery plan for the truck and drones operating in tandem with the objective of minimizing the total operational cost including the vehicles’ operating and waiting costs. Unlike most studies in the literature where the objective is to minimize completion time, which means one needs to know only the arrival time of the latest arriving vehicle (truck or drone) at each synchronization point, we need to keep track of all the individual waiting times of the truck and the drones to properly account for waiting costs, which makes it more challenging to handle the synchronization. We provide a flow based and two cut based mixed integer linear programming formulations strengthened with valid inequalities. For non-compact models, we devise a variety of branch-and-cut schemes to solve our problem to optimality. To compare our formulations/algorithms and to demonstrate their competitiveness, we conduct computational experiments on a range of instances. The results indicate the superiority of utilizing branch-and-cut methodology over a flow based formulation. We also use our model to conduct sensitivity analyses with several problem parameters and to explore the benefits of launch and retrieval at the same node, the tradeoff between the number of drones and the operational cost, and the special case with a minimize completion objective with one drone. We also document very low waiting times for drones in optimal solutions and show solutions from minimizing cost have much lower cost than those from minimizing makespan.
Embargo
Risk pooling under demand and price uncertainty
(Elsevier BV, 2023-11-22) Güllü, Refik; Erkip, Nesim
This paper studies purchasing a commodity or a perishable item under stochastically evolving and correlated prices for a distribution system environment. We consider the central purchasing of the commodity under the demand process correlated with the random price and decide on the timing and quantity of allocation to demand locations. As an implementation of the physical pooling concept, we investigate the benefits of pooling price and demand risk when the forward purchase is realized for all demand locations. We also study the benefits of informational pooling concepts by deciding on the allocation timing. Even when the demand locations are independent entities, organizing joint purchasing of a commodity may take advantage of economies of scale with a more reliable and less expensive delivery option. We develop a model to guide the purchasing and allocation of quantities and employ multi-echelon inventory theory methods and stochastic processes commonly used in financial engineering and operations management literature.
Embargo
Drones for relief logistics under uncertainty after an earthquake
(Elsevier BV, 2023-03-03) Dükkancı, Okan; Koberstein, Achim; Kara, Bahar Y.
This study presents a post-disaster delivery problem called the relief distribution problem using drones under uncertainty, in which critical relief items are distributed to disaster victims gathered at assembly points after a disaster, particularly an earthquake. Because roads may be obstructed by debris after an earthquake, drones can be used as the primary transportation mode. As the impact of an earthquake cannot be easily predicted, the demand and road network uncertainties are considered. Additionally, the objective is to minimize the total unsatisfied demand subject to a time-bound constraint on the deliveries, as well as the range and capacity limitations of drones. A two-stage stochastic programming and its deterministic equivalent problem formulations are presented. The scenario decomposition algorithm is implemented as an exact solution approach. To apply this study to real-life applications, a case study is conducted based on the western (European) side of Istanbul, Turkey. The computational results are used to evaluate the performance of the scenario decomposition algorithm and analyze the value of stochasticity and the expected value of perfect information under different parametric settings. We additionally conduct sensitivity analyses by varying the key parameters of the problem, such as the time-bound and capacities of the drones.
Open Access
A mean-CVaR approach to the risk-averse single allocation hub location problem with flow-dependent economies of scale
(Elsevier Ltd, 2022-11-29) Ghaffarinasab, Nader; Çavuş, Ö.; Kara, B. Y.
The hub location problem (HLP) is a fundamental facility planning problem with various applications in transportation, logistics, and telecommunication systems. Due to strategic nature of the HLP, considering uncertainty and the associated risks is of high practical importance in designing hub networks. This paper addresses a risk-averse single allocation HLP, where the traffic volume between the origin–destination (OD) pairs is considered to be uncertain. The uncertainty in demands is captured by a finite set of scenarios, and a flow-dependent economies of scale scheme is used for transportation costs, modeled as a piece-wise concave function of flow on all network arcs. The problem is cast as a risk-averse two-stage stochastic problem using mean-CVaR as the risk measure, and a novel solution approach combining Benders decomposition and scenario grouping is proposed. An extensive set of computational experiments is conducted to study the effect of different input parameters on the optimal solution, and to evaluate the performance of the proposed solution algorithm. Managerial insights are derived and presented based on the obtained results.
Open Access
Compound Poisson disorder problem with uniformly distributed disorder time
(Bernoulli Society for Mathematical Statistics and Probability, 2023-08) Uru, C.; Dayanık, Savaş; Sezer, Semih O.
Suppose that the arrival rate and the jump distribution of a compound Poisson process change suddenly at an unknown and unobservable time. We want to detect the change as quickly as possible to take counteractions, e.g., to assure top quality of products in a production system, or to stop credit card fraud in a banking system. If we have no prior information about future disorder time, then we typically assume that the disorder is equally likely to happen any time – or has uniform distribution – over a long but finite time horizon. We solve this so-called compound Poisson disorder problem for the practically important case of unknown, unobserved, but uniformly distributed disorder time. The solution hinges on the complete separation of information flow from the hard time horizon constraint, by describing the former with an autonomous time-homogeneous one-dimensional Markov process in terms of which the detection problem translates into a finite horizon optimal stopping problem. For any given finite horizon, the solution is two-dimensional. For cases where the horizon is large and one is unwilling to set a fixed value for it, we give a one-dimensional approximation. Also, we discuss an extension where the disorder may not happen on the given interval with a positive probability. In this extended model, if no detection decision is made by the end of the horizon, then a second level hypothesis testing problem is solved to determine the local parameters of the observed process.
Open Access
Graph neural networks for deep portfolio optimization
(Springer, 2023-07-22) Ekmekcioğlu, Ömer; Pınar, Mustafa Çelebi
There is extensive literature dating back to the Markowitz model on portfolio optimization. Recently, with the introduction of deep models in finance, there has been a shift in the trend of portfolio optimization toward data-driven models, departing from the traditional model-based approaches. However, deep portfolio models often encounter issues due to the non-stationary nature of data, giving unstable results. To address this issue, we advocate the utilization of graph neural networks to incorporate graphical knowledge and enhance model stability, thereby improving results in comparison with state-of-the-art recurrent architectures. Moreover, we conduct an analysis of the algorithmic risk-return trade-off for deep portfolio optimization models, offering insights into risk for fully data-driven models. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
Open Access
Free resolutions for the tangent cones of some homogeneous pseudo symmetric monomial curves
(Ankara University, 2023-03-30) Şahin, Nil
In this article, we study minimal graded free resolutions of Cohen-Macaulay tangent cones of some monomial curves associated to 4-generated pseudo symmetric numerical semigroups. We explicitly give the matrices in these minimal free resolutions.
Open Access
A planar facility location–allocation problem with fixed and/or variable cost structures for rural electrification
(2023-06) Akbaş, Beste; Kocaman, Ayşe Selin
One major impediment to developing countries’ economic growth is the lack of access to affordable, sustainable, and reliable modern energy systems. Even today, hundreds of millions of people live in rural areas and do not have access to essential electricity services. In this study, we present a planar facility location–allocation problem for planning decentralized energy systems in rural development. We consider nano-grid and micro-grid systems to electrify rural households. While micro-grids serve multiple households with a common generation facility, nano-grids are small-scale systems serving individual consumers. The households served by micro-grids are connected to the generation facilities with low-voltage cables, for which we employ a distance limit constraint due to technical concerns, including power loss and allowable voltage levels. In this problem, we minimize the total investment cost that consists of the facility opening and the low-voltage cable costs. In order to capture the diversity of cost structures in renewable energy investments, we consider three versions of the objective function where we incorporate different combinations of fixed and variable cost components for facilities. For this problem, we provide mixed-integer quadratically constrained problem formulations and propose model-based and clustering-based heuristic approaches. Model-based approaches are multi-stage, in which we solve the discrete counterparts of the problem and employ alternative selection methods for the candidate facility locations. Clustering-based approaches utilize faster clustering techniques to identify the type and location of the facilities. We conduct computational experiments on real-life instances from villages in Sub-Saharan Africa and perform a comparative analysis of the suggested heuristic approaches.
Open Access
A new formulation and an effective matheuristic for the airport gate assignment problem
(Elsevier, 2023-03) Karsu, Özlem; Solyalı, Oğuz
This study considers an airport gate assignment problem where a set of aircraft arriving to an airport are assigned to the fixed gates of the airport terminal or to the apron. The aim is to lexicographically minimize the number of aircraft assigned to the apron, and then the total walking distance by passengers. A new mixed integer linear programming formulation and a matheuristic is proposed for the problem. The proposed formulation is based on the idea of flow of passengers and has smaller size compared to the existing formulations in the literature. The proposed matheuristic, which relies on solving a restricted version of the proposed formulation of the problem, is not only easy to implement but is also very effective. A computational study performed on benchmark instances reveals that the proposed formulation and the matheuristic outperform the existing exact and heuristic algorithms in the literature.
Open Access
Humanitarian logistics under uncertainty: planning for sheltering and evacuation
(Springer Cham, 2023-05-09) Bayram, V.; Y. Kara, Bahar; Saldanha-da-Gama, F.; Yaman, H.; Eiselt, H. A.; Marianov, V.
This chapter focuses on a major area emerging in the context of humanitarian logistics: emergency evacuation planning and management. Two major aspects are covered: shelter site location and evacuation traffic assignment. Both are discussed separately before an integrated problem is considered. Throughout the chapter, uncertainty in the underlying parameters is assumed. The major sources of uncertainty analyzed are the demand for sheltering and capacity of the edges in the underlying network. Congestion issues emerge in this context that are also considered. Different paradigms for capturing uncertainty are considered for illustrative purposes, namely, robust optimization, chance-constrained programming, and stochastic programming.
Open Access
On the Hilbert series of the tangent cones for some 4-generated pseudosymmetric monomial curves
(TÜBİTAK, 2023-01-01) Şahin, Nil
In this article, we study Hilbert series of non-Cohen-Maculay tangent cones for some 4-generated pseudosymmetric monomial curves. We show that the Hilbert function is nondecreasing by explicitly computing it. We also compute standard bases of these toric ideals.