Scholarly Publications - Industrial Engineering

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

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Open Access
Learning the pareto set under incomplete preferences: pure exploration in vector bandits
(2024-11-26) Karagözlü, Efe Mert; Yıldırım, Yaşar Cahit; Ararat, Çagın; Tekin, Cem; Dasgupta, S; Mandt, S; Li, Y
We study pure exploration in bandit problems with vector-valued rewards, where the goal is to (approximately) identify the Pareto set of arms given incomplete preferences induced by a polyhedral convex cone. We address the open problem of designing sampleefficient learning algorithms for such problems. We propose Pareto Vector Bandits (PaVeBa), an adaptive elimination algorithm that nearly matches the gap-dependent and worst-case lower bounds on the sample complexity of (., d)-PAC Pareto set identification. Finally, we provide an in-depth numerical investigation of PaVeBa and its heuristic vari-ants by comparing them with the state-of-the-art multi-objective and vector optimization algorithms on several real-world datasets with conflicting objectives.
Open Access
A literature review on inventory pooling with applications
(MDPI AG, 2025-01-20) Yılmaz, Özlem
In this paper, we provide a review of academic research on inventory pooling published between 2010 and 2024, with a particular emphasis on studies that focus on real-world applications. The review analyzes the research conducted over the past 14 years, evaluates the outcomes of these applied studies, and identifies gaps in the literature. The contribution of this work is twofold: firstly, it provides insights into the extent to which theoretical advancements in inventory pooling have been implemented in the practice; secondly, it provides practitioners with an overview of recent real-world applications across various industrial contexts. The findings highlight the impact of inventory pooling on cost savings, service level improvements, inventory optimization in diverse sectors, and sustainability. Additionally, this paper examines the contributions of inventory pooling to economic, environmental, and social sustainability, offering a comprehensive analysis of its role in fostering sustainable practices across supply chains. Finally, the paper discusses practical challenges encountered in implementation and suggests directions for future research in this domain.
Open Access
An integrated price- and incentive-based demand response program for smart residential buildings: a robust multi-objective model
(Elsevier BV, 2024-10-15) Talebi, Hossein; Kazemi, Aliyeh; Shakouri, G. Hamed; Kocaman, Ayşe Selin; Caldwell, Nigel
Residential buildings consume a significant amount of energy, emphasizing the importance of optimizing energy usage. Demand-side management (DSM) helps consumers and producers manage energy consumption through incentives and pricing. This study develops a new mathematical model to manage DSM in smart residential buildings. Extant literature commonly considers only a single objective function, ignores uncertainties, and applies only one price- or incentive-based program to load management in smart residential buildings. This study develops a multi-objective mixed-integer linear programming (MILP) model that applies both price- and incentive-based programs and considers uncertainties. The objectives are cost reduction, peak load minimization, user comfort improvement, and load factor maximization. This model can manage optimal schedules for household appliances and power exchange within buildings. The study shows that participating in the incentive-based program in a four-household residential complex yielded a 2 % decrease in electricity costs and a 1 % reduction in peak load while upholding comfort and load factor levels compared to non-participation. When extended to an eight-household complex, potential benefits include an 8.3 % decrease in electricity cost and a 2.6 % reduction in peak load, highlighting the program’s effectiveness in residential energy management strategies.
Open Access
Point cloud registration with quantile assignment
(Springer, 2024-03-19) Oğuz, Ecenur; Doğan, Yalım; Güdükbay, Uğur; Karaşan, Oya; Pınar, Mustafa
Point cloud registration is a fundamental problem in computer vision. The problem encompasses critical tasks such as feature estimation, correspondence matching, and transformation estimation. The point cloud registration problem can be cast as a quantile matching problem. We refined the quantile assignment algorithm by integrating prevalent feature descriptors and transformation estimation methods to enhance the correspondence between the source and target point clouds. We evaluated the performances of these descriptors and methods with our approach through controlled experiments on a dataset we constructed using well-known 3D models. This systematic investigation led us to identify the most suitable methods for complementing our approach. Subsequently, we devised a new end-to-end, coarse-to-fine pairwise point cloud registration framework. Finally, we tested our framework on indoor and outdoor benchmark datasets and compared our results with state-of-the-art point cloud registration methods.
Open Access
Optimizing vaccine delivery with drones for hard-to-reach regions
(I E E E Computer Society, 2024-01-06) Campbell, James F.; Kara, Bahar; Li, Haitao; Enayati, Shakiba; Peker, Meltem; Akenroye, Temi
This research optimizes the use of drones, alongside other transport modes, for delivery of routine childhood vaccines subject to cold chain requirements. We focus on the value of drones to improve vaccine deliveries for hard-to-reach regions. This paper first briefly describes optimization of country-level vaccine distribution from national depots to local health zone distributions centers (DCs) using both large and small drones, along with boats, trucks and planes. Then we focus on research on optimizing local vaccine delivery within one health zone, from the DC to remote aid posts, using small drones, along with walking, boats and trucks. Results using data for the island nation of Vanuatu show that drones can be very useful for vaccine delivery to replace current transportation options, and to resupply health workers with fresh vaccines at remote sites to allow more efficient health worker outreach trips. © 2024 IEEE Computer Society. All rights reserved.
Embargo
The impact of pumped hydro energy storage configurations on investment planning of hybrid systems with renewables
(Elsevier Ltd, 2024-02) Yurter, Gülin; Nadar, Emre; Kocaman, Ayşe Selin
The pumped hydro energy storage (PHES) systems can be installed in various configurations depending on the specific geographical and hydrological conditions. Closed-loop PHES systems are off-stream and have no natural inflow to the system. However, open-loop systems are on-stream and have natural inflows to the upper and/or lower reservoirs. In this study, we develop two-stage stochastic programming models for various PHES configurations to investigate how the choice of PHES configuration impacts the sizing decisions and costs of a hybrid system that includes a renewable power generator co-operated with PHES. Our numerical results show that using a PHES facility instead of a conventional hydropower system reduces the expected system cost and mismatched demand significantly. Open-loop PHES facilities perform better than closed-loop PHES and seawater-PHES facilities, dramatically lowering the need for fossil fuels in demand fulfillment. The most cost-efficient PHES configuration is when there is natural inflow to the upper reservoir. Using solar energy instead of wind as the renewable source significantly increases the requirement for larger upper reservoirs in on-stream open-loop PHES facilities, while reducing the expected system cost for all configurations.
Embargo
A unifying framework for selective routing problems
(Elsevier, 2025-01-01) Dursunoğlu, Çağla Fatma; Arslan, Okan; Demir, Şebnem Manolya; Yetiş Kara, Bahar; Laporte, Gilbert
We present a unifying framework for Selective Routing Problems (SRPs) through a systematic analysis. The common goal in SRPs is to determine an optimal vehicle route to serve a subset of vertices while covering another subset. They arise in diverse fields such as logistics, public health, disaster response, and urban development. To establish a unifying framework for different but related problems, we associate the notion of service with coverage and argue that routing is a tool of service. We classify SRPs according to their selectiveness degree and emphasize the breadth and depth of this problem in terms of its characteristics. This SRP framework helps us identify research gaps as well as potential future research areas. We present a generic mathematical model, use it to describe the connections among these problems and identify some identical problems presented under different names.
Open Access
Convergence analysis of a norm minimization-based convex vector optimization algorithm
(Society for Industrial and Applied Mathematics, 2024-07-25) Ararat, Çağın; Ulus, Firdevs; Umer, Muhammad
In this work, we propose an outer approximation algorithm for solving bounded convex vector optimization problems (CVOPs). The scalarization model solved iteratively within the algorithm is a modification of the norm-minimizing scalarization proposed in [\c C. Ararat, F. Ulus, and we prove that the algorithm terminates after finitely many iterations, and it returns a polyhedral outer approximation to the upper image of the CVOP such that the Hausdorff distance between the two is less than \epsilon . We show that for an arbitrary norm used in the scalarization models, the approximation error after k iterations decreases by the order of O(k1/(1-q)), where q is the dimension of the objective space. An improved convergence rate of O(k2/(1-q)) is proved for the special case of using the Euclidean norm.
Embargo
One-dimensional bin packing with pattern-dependent processing time
(Elsevier B.V., 2025-05-01) Marinelli, Fabrizio; Pizzuti, Andrea; Wu, Wei; Yagiura, Mutsunori
In this paper the classical one-dimensional bin packing problem is integrated with scheduling elements: a due date is assigned to each item and the time required to process each bin depends on the pattern being used. The objective is to minimize a convex combination of the material waste and the delay costs, both significant in many real-world contexts. We present a novel pattern-based mixed integer linear formulation suitable for different classical scheduling objective functions, and focus on the specific case where the delay cost corresponds to the maximum tardiness. The formulation is tackled by a branch-and-price algorithm where the pricing of the column generation scheme is a quadratic problem solved by dynamic programming. A sequential value correction heuristic (SVC) is used to feed with warm starting solutions the column generation which, in turn, feeds the SVC with optimal prices so as to compute refined feasible solutions during the enumeration. Computational tests show that both column generation and branch-and-price substantially outperform standard methods in computing dual bounds and exact solutions. Additional tests are presented to analyze the sensitivity to parameters’ changes.
Open Access
Correction to: Asymptotically optimal Bayesian sequential change detection and identification rules
(2024) Dayanık, Savaş; Powell, W. B.; Yamazaki, K.
The article Asymptotically optimal Bayesian sequential change detection and identification rules, written by Savas Dayanik, Warren B. Powell, Kazutoshi Yamazaki, was originally published electronically on the publisher’s internet portal on 12 April, 2012 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 02 Sept, 2021 to © The Author(s). Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Open Access
Short communication: on the separability of vector-valued risk measures
(Society for Industrial and Applied Mathematics, 2024-10-24) Ararat, Çağın; Feinstein, Zachary
Risk measures for random vectors have been considered in multiasset markets with transaction costs and financial networks in the literature. While the theory of set-valued risk measures provides an axiomatic framework for assigning to a random vector its set of all capital requirements or allocation vectors, the actual decision-making process requires an additional rule to select from this set. In this paper, we define vector-valued risk measures by an analogous list of axioms and show that, in the convex and lower semicontinuous case, such functionals always ignore the dependence structures of the input random vectors. We also show that set-valued risk measures do not have this issue as long as they do not reduce to a vector-valued functional. Finally, we demonstrate that our results also generalize to the conditional setting. These results imply that convex vector-valued risk measures are not suitable for defining capital allocation rules for a wide range of financial applications including systemic risk measures.
Open Access
Productivity enhancement in top-down VPP via concurrent grayscaling and platform speed profile optimization for symmetrical parts having micro scale features
(Springer, 2024-06-14) Güven, Ege; Karpat, Yiğit; Çakmakcı, Melih
Vat Photopolymerization (VPP), a widely adopted additive manufacturing technique, has revolutionized the domain of 3D printing by enabling the precise fabrication of complex structures, including intricate details. However, challenges remain in achieving optimal print quality while improving speed. Conventionally, grayscaling has been used to improve part accuracy in continuous VPP systems as the build platform speed remains constant. Considering a detailed photocurable resin solidification model, together with grayscaling, this study aims to improve productivity by optimizing platform speed profile while maintaining the build quality. While the optimization formulation presented here can be applied to any part, the computational limitations due to the employment of a voxel-based approach and the nonlinear nature of the resulting optimization problem are simplified by adopting a novel discretization methodology utilizing the symmetric properties of the target 3D part. By employing ring elements instead of voxels for cylindrical symmetrical parts, the computational load of the optimization algorithm is dramatically reduced. Experimental results show the proposed concurrent optimization reduces print time by 56% while maintaining superior print surface quality on an hourglass-shaped test part having micro scale features.
Open Access
No country for young refugees: barriers and opportunities for inclusive refugee education practices
(Sage Publications, Inc., 2024) Demir, Sebnem Manolya; Sahinyazan, Feyza G.; Kara, Bahar Yetiş; Buluc, Elfe
The recent refugee crises in Ukraine (2022) and Syria (2011) have created millions of refugees, 40% of whom are children. The education systems of countries hosting refugees struggle to integrate such large populations. In addition, language barriers and the stigma associated with refugees hamper inclusive and equitable education opportunities for these children. There is thus a risk of "lost generations" distanced from education, who may eventually depend on social security systems and monetary aid in the long term. This study considers the following research question: How can a host country improve the inclusion of refugee children in the education system without overburdening its infrastructure? First, we document the availability and accessibility challenges and opportunities that refugee children face during the Syrian refugee crisis. We then develop an inclusive planning strategy aligned with existing capacity and resources and formulate two adaptations of the maximum covering problem (MCP): cooperative capacitated MCP with heterogeneity constraints (CCMCP-HC) to improve the current schooling access in T & uuml;rkiye and Modular CCMCP-HC to guide early planning in the case of a future crisis. Our computational analyses illustrate that the proposed approach yields higher schooling rates and capacity utilization than existing approaches. Our results emphasize the importance of having a planning strategy in the initial phases of a crisis that considers future integration possibilities. This study analyzes T & uuml;rkiye's experience and lessons learned to provide a road map for other ongoing and future refugee crises.
Embargo
Mathematical programming models for multistage rural electrification planning: Off-grid, grid and mini-grid options
(Pergamon-Elsevier Science Ltd., 2025-02-01) Yazıcı, Gözde; Karaşan, Oya Ekin; Kocaman, Ayşe Selin; Stoner, Rob
Approximately 9% of the global population lacks access to electricity. The majority of this population resides in rural areas, highlighting the critical importance of rural electrification efforts. In this study, we introduce novel mathematical programming models aimed at addressing the technology choice and network design challenges in rural electrification. These models determine the optimal electrification technology among off- grid, grid and mini-grid options for each demand point while designing the cost effective grid and mini-grid networks. Furthermore, we present multistage versions of these mathematical models, demonstrating the cost advantage of multistage modeling. These formulations can serve as a comprehensive framework that incorporates investment requirements for system roll-out. Through numerical experiments utilizing both real- life and synthetic instances, we offer new insights into electrification in diverse environments. Our research is expected to contribute to the socio-economic development of developing countries and aid in achieving the targets outlined in Sustainable Development Goal 7.
Open Access
MAD risk parity portfolios
(Springer New York LLC, 2024-01-16) Ararat, Çağın; Cesarone, F.; Pınar, Mustafa Çelebi; Ricci, J. M.
In this paper, we investigate the features and the performance of the risk parity (RP) portfoliosusing the mean absolute deviation (MAD) as a risk measure. The RP model is a recent strategyfor asset allocation that aims at equally sharing the global portfolio risk among all the assetsof an investment universe. We discuss here some existing and new results about the propertiesof MAD that are useful for the RP approach. We propose several formulations for finding MAD-RP portfolios computationally, and compare them in terms of accuracy and efficiency. Furthermore, we provide extensive empirical analysis based on three real-world datasets, showing that the performances of the RP approaches generally tend to place both in termsof risk and profitability between those obtained from the minimum risk and the Equally Weighted strategies.
Open Access
Unraveling the complex interplay between elastic recovery, contact pressure, and friction on the flank face of the micro tools via plunging-type testing
(Elsevier Inc., 2024-07-06) Karpat, Yiğit; Güven, Can
A good understanding of the interplay between the cutting tool edge radius, elastic recovery, friction, and contact pressure is essential for better modeling of ploughing forces during micro-scale cutting. This study conducts plunging tests on an ultra-precision CNC with engineered tungsten carbide cutting tools on commercially pure titanium alloy. The cutting tool edge radius is prepared to be around 3.5-4 mu m, which resembles those cutting tools used in micro scale machining. During plunging tests, the micro cutting tool is given a sinusoidal movement with an amplitude close to edge radius of the tool as the work material is rotated at a constant speed. The residual depth profiles of the webs corresponding to the commanded depths were investigated in detail to identify elastic recovery rate. The cutting and thrust force measurements during plunging experiments together with identified elastic recovery rate was employed in an analytical model of micro scale machining to obtain the variations of contact pressure and coefficient of friction as a function of commanded depth. Due to the scale of the experiments that were performed, the effects of surface topography of the cutting tool and possible alignment errors are also considered in the analytical model. A linear relationship between the contact pressure and elastic recovery has been identified during ploughing-dominated machining conditions for the work material and the cutting tool pair considered in this study. The proposed experimental technique is shown to be promising in terms of modeling ploughing forces during micro-scale cutting.
Embargo
Facility location decisions for drone delivery with riding: a literature review
(Elsevier Ltd, 2024-07) Dükkancı, O.; Campbell, J.F.; Yetiş Kara, Bahar
This study presents a comprehensive literature survey on facility location problems for drone (uncrewed vehicle) delivery in situations where drones can ride in or on other vehicles. This includes facilities visited by only one type of vehicle, as well as facilities visited by both drones and other vehicles. Unlike traditional facility location problems for delivery systems with one vehicle type, hybrid vehicle-drone delivery systems usually require determining locations where the two vehicle types meet and separate. The main goals of this paper are to review the large volume of drone delivery literature with riding from a facility location perspective to provide a connection between the studies from different research areas that cover similar problems, and to highlight future research directions in this area. We first review the functions of drones, including aerial and ground drones, and the different types of facilities used for hybrid vehicle-drone delivery systems. The literature is categorized based on the presence of resupply operations, the locations of drone launch and retrieval points, the types of drones (aerial or ground) and the location space (discrete or continuous). Each category is analyzed in terms of the modeling approach, decision(s), objective function(s), constraints and additional features. The paper concludes with promising future research directions.
Embargo
Finding robustly fair solutions in resource allocation
(Elsevier Ltd, 2025-02) Karsu, Özlem; Elver, İzzet Egemen; Kınık, Tuna Arda
In this study, we consider resource allocation settings where the decisions affect multiple beneficiaries and the decision maker aims to ensure that the effect is distributed to the beneficiaries in an equitable manner. We specifically consider stochastic environments where there is uncertainty in the system and propose a robust programming approach that aims at maximizing system efficiency while guaranteeing an equitable benefit allocation even under the worst scenario. Acknowledging the fact that the robust solution may lead to high efficiency loss and may be over-conservative, we adopt a parametric approach that allows controlling the level of conservatism and present the decision maker alternative solutions that reveal the trade-off between efficiency and the degree of conservatism when incorporating fairness. We obtain tractable formulations, leveraging the results we provide on the properties of highly unfair allocations. We demonstrate the usability of our approach on project selection and shelter allocation applications.
Open Access
Sparsity penalized mean–variance portfolio selection: analysis and computation
(SPRINGER HEIDELBERG, 2024-11-25) Şen, Buse; Akkaya, Deniz; Pınar, Mustafa Çelebi
We consider the problem of mean–variance portfolio selection regularized with an -penalty term to control the sparsity of the portfolio. We analyze the structure of local and global minimizers and use our results in the design of a Branch-and-Bound algorithm coupled with an advanced start heuristic. Extensive computational results with real data as well as comparisons with an off-the-shelf and state-of-the-art (MIQP) solver are reported.
Open Access
On the monotonicity of the Hilbert functions for 4-generated pseudo-symmetric monomial curves
(Taylor & Francis Inc., 2024-07-14) Şahin, Nil
In this article we solve the following problem: “The Hilbert function of thelocal ring of a 4-generated pseudo-symmetric numerical semigroup is alwaysnon-decreasing.” We give a complete characterization of the standard baseswhen the tangent cone is not Cohen-Macaulay by showing that the number ofelements in the standard basis depends on some parameters we define. Sincethe tangent cone is not Cohen-Macaulay, non-decreasingness of the Hilbertfunction was not guaranteed, thus we proved the non-decreasingness fromour explicit Hilbert function computation.