Mehmet A. Begen

• Naderi, B.; Begen, M. A.; Zaric, G. S., (Forthcoming), "Type-2 integrated process-planning and scheduling problem: Reformulation and solution algorithms", Computers and Operations Research
  Abstract: We study the type-2 integrated process-planning and scheduling (IPPS) problem where each job is represented by a directed network graph. To the best of our knowledge, there is only one mathematical model in the literature implementing the type-2 IPPS partially, and the solution methods available for this problem are all based on heuristics and metaheuristics. We introduce three properties that enable us to fully formulate all aspects of the type-2 IPPS problem with a mathematical programming model for the first time. To solve our model, we develop a logic-based Benders decomposition method hybridized with constraint programming. We decompose the problem into two smaller ones such that we can use the best solution technique for each one, master problem and subproblem. To enhance our solution approach, we incorporate a combinatorial relaxation of subproblem into the master problem. We evaluate our method using a well-known benchmark including 24 instances and compare its performance with six existing solution methods solving the same benchmark. We solve all the 24 instances of this benchmark to optimality where seven of these 24 instances are solved to optimality for the first time. We also generate a new set of 144 larger instances to further evaluate our solution methods and provide insights on when each method performs better.
• Zacharias, C.; Liu, N.; Begen, M. A., (Forthcoming), "Dynamic Inter-day and Intra-day Scheduling", Operations Research
  Abstract: The simultaneous consideration of appointment day (inter-day scheduling) and time of day (intra-day scheduling) in dynamic scheduling decisions is an important theoretical and practical problem that has remained open due to its stochastic nature, complex structure, and large dimensionality. We introduce a novel dynamic programming framework that incorporates jointly these scheduling decisions in two timescales. Our model is designed with the intention of bridging the two streams of literature on inter-day and intra-day scheduling, and to leverage their latest theoretical developments in tackling the joint problem. We build upon two recent studies: one from dynamic inter-day scheduling (Truong 2015), and one from static intra-day scheduling (Zacharias and Yunes 2020). We establish connections between these two studies by proving novel theoretical results in discrete convex analysis regarding constrained multimodular function minimization. Grounded on our theory, we develop a practically implementable and computationally tractable scheduling paradigm with performance guarantees. Numerical experiments demonstrate that the optimality gap is less than 1% for practical instances of the problem.

  Link(s) to publication:

  https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3728077

  http://dx.doi.org/10.2139/ssrn.3728077

• Begen, M. A.; Okuyan, H. M., (Forthcoming), "LncRNAs in Osteoarthritis", Clinica Chimica Acta
  Abstract: Osteoarthritis (OA) is a progressive joint disease that affects millions of older adults around the world. With increasing rates of incidence and prevalence worldwide, OA has become an enormous global socioeconomic burden on healthcare systems. Long non-coding ribonucleic acids (lncRNAs), essential functional molecules in many biological processes, are a group of non-coding RNAs that are greater than approximately 200 nucleotides in length. Fast-growing and recent developments in lncRNA research are captivating and represent a novel and promising field in understanding the complexity of OA pathogenesis. The involvement of lncRNAs in OA’s pathological processes and their altered expressions in joint tissues, blood and synovial fluid make them attractive candidates for the diagnosis and treatment of OA. We focus on the recent advances in major regulator mechanisms of lncRNAs in the pathophysiology of OA and discuss potential diagnostic and therapeutic uses of lncRNAs for OA. We investigate how upregulation or downregulation of lncRNAs influences the pathogenesis of OA and how we can use lncRNAs to elucidate the molecular mechanism of OA. Furthermore, we evaluate how we can use lncRNAs as a diagnostic marker or therapeutic target for OA. Our study not only provides a comprehensive review of lncRNAs regarding OA’s pathogenesis but also contributes to the elucidation of its molecular mechanisms and to the development of diagnostic and therapeutic approaches for OA.
• Naderi, B.; Begen, M. A.; Zaric, G. S.; Roshanaei, V., (Forthcoming), "A Novel and Efficient Exact Technique for Integrated Staffing, Assignment, Routing, and Scheduling of Home Care Services Under Uncertainty", Omega-International Journal of Management Science
  Abstract: We model and solve an integrated multi-period staffing, assignment, routing, and scheduling for home care services under uncertainty. The goal is to construct a weekly schedule that adheres to related operational considerations and determines optimal staffing of caregivers by minimizing caregivers’ fixed- and overtime costs. For tractability, we incorporate a priori generated visit patterns—an existing practical approach that deals effectively with hard assignment decisions in. First, we propose a novel mixed-integer program (MIP) for the nominal problem. We then incorporate uncertainty in service and travel times and develop a robust counterpart by hybridizing interval and polyhedral uncertainty sets. Second, we show that there is a special mathematical structure within the model that allows us to develop a novel logic-based Benders branching-decomposition algorithm that systematically delays the resolution of difficult routing/ scheduling problems and efficiently solves both the nominal and robust MIP models. Using a dataset from the literature, we show that CPLEX can solve our nominal and robust models with an average optimality gaps of 44.56% and 45.53%, respectively. Using the same dataset, we demonstrate that our new exact technique can solve our nominal and robust mixed-integer models to an average optimality gap of 2.8% and 4.5%, respectively. Third, we provide practical insights into (i) the price of robustness and (ii) the impacts of nurse flexibility and overtime. The average total cost does not increase beyond 12.7% than the nominal solution and the cost-savings of nurse flexibility is approximately five times higher than that of overtime.

  Link(s) to publication:

  https://www.sciencedirect.com/journal/omega

  http://dx.doi.org/10.2139/ssrn.3836827

• Okuyan, C. B.; Caglar, S.; Begen, M. A., 2022, "How does the COVID-19 pandemic influence educational and psychological health of nursing students in Turkey: What can be done to minimize adverse effects of the pandemic?", Technium Education and Humanities, September 2(4): 63 - 72.
  Abstract: We evaluate the effects of the COVID-19 pandemic on the educational processes, and psychological health of nursing students and provide an overview of the measures that should be taken against minimizing the adverse effects of the pandemic. We find that nursing students experience anxiety and stress during the pandemic due to online education and social isolation. Social media-based health education planning (provided by nursing trainers) and inclusion of online simulation applications to the curriculum can be effective ways to prevent the negative effects of the pandemic on education of nursing students and to protect students' health and ensure that they gain necessary nursing skills as in formal education.

  Link(s) to publication:

  https://techniumscience.com/index.php/education/article/view/7483

• Begen, M. A.; Bayley, T.; Rodrigues, F. F.; Barrett, D., 2022, "Relative Efficiency of Radiation Treatment Centres: An Application of Data Envelopment Analysis", Healthcare, June 10(6): 1033 - 1033.
  Abstract: We evaluate a number of cancer treatment centres in Ontario and determine their relative efficiency so that their performance can be compared against the provincial targets by taking into account the differences among them. These differences can be in physical and financial resources, and patient demographics. We develop an analytical framework based on a three- step data envelopment analysis (DEA) model to build efficiency metrics for planning, delivery, and quality of treatment at each centre, use regression analysis to explain our efficiency metrics, and demonstrate how our findings can inform continuous improvement efforts.

  Link(s) to publication:

  https://www.mdpi.com/2227-9032/10/6/1033

  http://dx.doi.org/10.3390/healthcare10061033

• Okuyan, C. B.; Begen, M. A., (Forthcoming), "Working from Home During the COVID-19 Pandemic, its Effects on Health, and Recommendations: The Pandemic and Beyond", Perspectives In Psychiatric Care
  Abstract: Purpose: We provide an overview of how to work from home during the COVID-19 pandemic, and what measures should be taken to minimize the negative effects of working from during this time. Conclusions: The COVID-19 pandemic has forced an adaptation process for the whole world and working life. One of the most adaptation measures is working from home. Working from home comes with challenges and concerns but it also has its favorable aspects. Practice Implications: It is crucial to develop and implement best practices for working from home to maintain a good level of productivity, achieve the right level of work and life balance and maintain a good level of physical and mental health.

  Link(s) to publication:

  http://dx.doi.org/10.1111/ppc.12847

• Caglar Gencosman, B.; Begen, M. A., (Forthcoming), "Exact Optimization and Decomposition Approaches for Shelf Space Allocation", European Journal Of Operational Research
  Abstract: Shelf space is one of the scarcest resources, and its effective management to maximize profits has become essential to gain a competitive advantage for retailers. We consider the two-dimensional shelf space allocation problem (2DSSAP) with additional features motivated by literature and our interactions with a local bookstore. Two dimensions represent the width and height of rectangular arrangement space of a product. We determine optimal number of facings of all products in both dimensions and allocate them as contiguous rectangles to maximize profit. We first develop a mixed-integer linear mathematical programming model (MIP) for our problem and propose a solution method based on logic-based Benders decomposition (LBBD). Next, we construct an exact 2-stage algorithm (IP1/IP2), inspired by LBBD, which can handle larger and real-world size instances. To compare performances of our methods, we generate 100 test instances inspired by real-world applications and benchmarks from the literature. We observe that IP1/IP2 finds optimal solutions for real-world instances efficiently and can increase the local bookstore's profit up to 16.56%. IP1/IP2 can provide optimal solutions for instances with 100 products in minutes and optimally solve up to 250 products (assigned to 8 rows x 160 columns) within a time limit of 1800 seconds. This exact 2-stage IP1/IP2 solution approach can be effective in solving similar problems such as display problem of webpage design, allocation of product families in grocery stores, and flyer advertising.

  Link(s) to publication:

  http://dx.doi.org/10.1016/j.ejor.2021.08.047

• Naderi, B.; Roshanaei, V.; Begen, M. A.; Aleman, D.; Urbach, D., 2021, "Increased surgical capacity without additional resources: Generalized operating room planning and scheduling", Production and Operations Management, October 30(8): 2608 - 2635.
  Abstract: We study a generalized operating room planning and scheduling (GORPS) problem at the Toronto General Hospital (TGH) in Ontario, Canada. GORPS allocates elective patients and resources (i.e., operating rooms, surgeons, anesthetists) to days, assigns resources to patients, and sequences patients in each day. We consider patients’ due-date, resource eligibility, heterogeneous performances of resources, downstream unit requirements, and lag times between resources. The goal is to create a weekly surgery schedule that minimizes fixed- and over-time costs. We model GORPS using mixed-integer and constraint programming models. To efficiently and effectively solve these models, we develop new‘ multi-featured logic-based Benders decomposition approaches. Using data from TGH, we demonstrate that our best algorithm solves GORPS with an average optimality gap of 2.71% which allows us to provide our practical recommendations. First, we can increase daily OR utilization to reach 80%—25% higher than the status quo in TGH. Second, we do not require to optimize for the daily selection of anesthetists —this finding allows for the development of effective dominance rules that significantly mitigate intractability. Third, solving GORPS without downstream capacities (like many papers in literature) makes GORPS easier to solve, but such OR schedules are only feasible in 24% of instances. Finally, with existing ORs’ safety capacities, TGH can manage 40% increase in its surgical volumes. We provide recommendations on how TGH must adjust its downstream capacities for varying levels of surgical volume increases (e.g., current urgent need for more capacity due to the current Covid-19 pandemic).

  Link(s) to publication:

  http://dx.doi.org/10.1111/poms.13397

• Sang, P.; Begen, M. A.; Cao, J., 2021, "Appointment (Surgery) Scheduling with a Quantile Objective", Computers and Operations Research, August 132: 105295 - 105295.
  Abstract: Appointment scheduling has many applications (e.g., surgery scheduling, airport gate scheduling, container vessel dockings and radiation therapy bookings) and it has a direct and significant operational and economic impact. For example, in healthcare, surgical departments are one of the main drivers of hospital costs and revenue, and appointment scheduling is used to book surgeries. Effective scheduling not only enables patients' timely access to care but also enables more efficient operations. This becomes especially important as healthcare costs and demand are on the rise in many countries. We study appointment scheduling where there are jobs (e.g., patients, container vessels, airplanes) with random processing durations, an expensive processor (e.g., a doctor, dock crane, airport gate) and significant costs for processor idle time, processor overtime, and job waiting. The goal is to determine an appointment schedule that minimizes a measure of total costs as the objective. The appointment scheduling problem has been well studied in the literature with the expected cost objective. Almost all papers in the literature on appointment scheduling use the expected cost criterion, which may not be suitable when risk measures and/or service levels are considered. In this paper, we study this problem with a new objective: minimization of any quantile of the cost distribution, e.g., median, 90th percentile. We obtain theoretical results for some special cases and develop an algorithm for the general case. Our algorithm does not require a specific distribution assumption and can work directly with data samples. We present numerical examples with real data on surgeries. Our results show that allocated schedules based on the quantile objective with identical jobs are different than the ones generated by the expected cost objective and they do not show the well-known dome-shaped pattern but a semi-dome-shaped pattern which first increases (like the dome-shaped pattern) but then its decrease is not monotone (unlike the dome-shaped pattern). To the best of our knowledge, this is the first paper on appointment scheduling problem with the objective of the quantile function minimization.

  Link(s) to publication:

  http://dx.doi.org/10.1016/j.cor.2021.105295

• Okuyan, C. B.; Begen, M. A., 2021, "Why are Elderly at Higher Risk and what should be done for them During the COVID-19 pandemic", International Journal of Caring Sciences, April 14(1): 767 - 767.
  Abstract: Coronavirus disease 2019 (COVID-19) is caused by an enveloped RNA virus seen in humans and animals. This rapidly progressing disease has become a pandemic and it has direct adverse effects on humans and healthcare systems around the world. Based on initial findings and observations gathered during the COVID-19 pandemic around the world, this disease mainly affects elderly people with Alzheimer’s or dementia, those with risk factors such as hypertension, diabetes or cardiovascular disease (CVD), and individuals with respiratory tract diseases or disorders due to ageing, physiologic changes and underlying potential health conditions. Understanding the present and potential effects of the pandemic on elderly may assist to improve their care and quality of life. These factors may also affect individuals and health professionals providing care for elderly. In this paper, we aim to discuss why elderly people are at higher risk, what should they pay attention to and what should be done for them during the COVID-19 pandemic.

  Link(s) to publication:

  http://www.internationaljournalofcaringsciences.org/Issue.aspx?issueID=60&pageIndex=0&pageReason=0

  http://www.internationaljournalofcaringsciences.org/docs/82_birimoglu_special_14_1.pdf

• Okuyan, H. M.; Dogan, S.; Terzi, Y. T.; Begen, M. A.; Turgut, F. H., 2021, "Association of serum lncRNA H19 expression with inflammatory and oxidative stress markers and routine biochemical parameters in chronic kidney disease", Clinical and Experimental Nephrology, February 25(5): 522 - 530.
  Abstract: Background: Chronic kidney disease (CKD) is a disorder that affects millions worldwide, and current treatment options aimed at inhibiting the progression of kidney damage are limited. Long noncoding RNA (lncRNA) H19 is one of the first explored lncRNAs and its deregulation is associated with renal pathologies such as renal cell injury and nephrotic syndrome. However, there is still no research investigating the connection between serum lncRNA H19 expressions and laboratory parameters and health outcomes in patients with CKD. Therefore, we investigate the relation of serum lncRNA H19 expressions with routine biochemical parameters, inflammatory cytokines, oxidative stress and mineralization markers in patients with advanced CKD.
  
  Methods: LncRNA H19 serum levels from 56 patients with CKD and 20 healthy controls were analyzed with real-time quantitative polymerase chain reaction method. Serum tumor necrosis factor-alpha (TNF-α), interleukin 6 (IL-6) and osteocalcin (OC) levels were measured by enzyme linked-immunosorbent assay. Total antioxidant status (TAS) and total oxidative status (TOS) levels were evaluated by the automated routine measurement method.
  
  Results: We found that lncRNA H19 expression were upregulated in patients with CKD compared to the healthy controls. Furthermore, lncRNA H19 relative expression levels showed a negative relationship with glomerular filtration rate (GFR) while it was positively correlated with ferritin, parathyroid hormone, TNF-α, IL-6, OC, TAS and TOS levels. Our findings revealed the association of increased serum lncRNA H19 expressions with estimated GFR, inflammation, and mineralization markers in CKD patients.
  
  Conclusions: lncRNA H19 expressions were increased in CKD stage 3-5 and HD patients and elevated lncRNA H19 expressions were associated with biochemical parameters involved in inflammation and mineralization.

  Link(s) to publication:

  https://link.springer.com/article/10.1007/s10157-021-02023-w

  http://dx.doi.org/10.1007/s10157-021-02023-w

• Okuyan, H. M.; Begen, M. A., 2021, "miRNAs as attractive diagnostic and therapeutic targets for Familial Mediterranean Fever", Modern Rheumatology, February 31(5): 949 - 959.
  Abstract: Familial Mediterranean Fever (FMF) is a hereditary early-onset disease that causes periodical fever attack, excessive release of IL-1β, serositis, arthritis and peritonitis. Genetic analyses conducted on FMF patients (mutated and non-mutated) have highlighted that additional contributing factors such as epigenetics and environment play a role in clinical manifestations of FMF. Recently researchers report that microRNAs (miRNAs), implicated in epigenetic mechanisms, may contribute to the pathogenesis of FMF. miRNAs, a member of the captivating noncoding RNA family, are the single-strand transcripts that work in physiological and pathophysiological processes by regulating target gene expression. Recent studies have shown that miRNAs are associated with various mechanisms involved in the pathogenesis of FMF, such as apoptosis, inflammation and autophagy. Moreover, these miRNAs molecules might have potential use in treatment, therapeutic response monitoring and the diagnosis of subtypes of the disease in the future. Motivated with these potential benefits (diagnostic and therapeutic) of miRNAs, we focus on recent advances of clinical significances and potential action mechanisms of miRNAs in FMF pathogenesis and discuss their potential use for FMF.

  Link(s) to publication:

  http://dx.doi.org/10.1080/14397595.2020.1868674

• Habbous, S.; Barnieh, L.; Klarenbach, S.; Manns, B.; Sarma, S.; Begen, M. A.; Litchfield, K.; Lentine, K. L.; Singh, S.; Garg, A. X., et al., 2020, "Evaluating multiple living kidney donor candidates simultaneously is more cost-effective than sequentially.", Kidney International, December 98(6): 1578 - 1588.
  Abstract: When multiple living donor candidates come forward to donate a kidney to the same recipient, some living donor programs evaluate one candidate at a time to avoid unnecessary evaluations. Evaluating multiple candidates concurrently rather than sequentially may be cost-effective from a health care system perspective if it reduces the time recipients spend on dialysis. We used a simple decision tree to estimate the cost-effectiveness of evaluating 2 to 4 candidates simultaneously rather than sequentially as potential kidney donors for the same intended recipient. Evaluating 2 donor candidates simultaneously cost $974 ($CAD) more than if they were evaluated sequentially, but living donation occurred 1 month earlier. This translated into $6,931 in averted dialysis costs and a total cost-savings of $5,957 per intended recipient. Simultaneous evaluations also resulted in 1% more living donor transplants. If recipients were free from dialysis at the start of donor candidate evaluations, simultaneous evaluations also reduced the rate of dialysis initiation by 2%. Benefits were also observed in the 3- and 4-candidate scenarios. In conclusion, living donor programs should consider evaluating up to 4 living donor candidates simultaneously when they come forward for the same recipient. Health care system costs incurred are more than offset by avoided dialysis costs.

  Link(s) to publication:

  http://dx.doi.org/10.1016/j.kint.2020.06.015

• Barzanji, R.; Naderi, B.; Begen, M. A., 2020, "Decomposition algorithms for the integrated process-planning and scheduling problem", OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, June 93
  Abstract: There are several algorithms to solve the integrated process planning and scheduling (IPPS) problem (i.e., flexible job shop scheduling with process plan flexibility) in the literature. All the existing algorithms for IPPS are heuristic-based search methods and no research has investigated the use of exact solution methods for this problem. We develop several decomposition approaches based on the logic-based Benders decomposition (LBBD) algorithm. Our LBBD algorithm allows us to partition the decision variables in the IPPS problem into two models, master-problem and sub-problem. The master-problem determines process plan and operation-machine assignment, while the sub-problem optimizes sequencing and scheduling decisions. To achieve faster convergence, we develop two relaxations for the optimal makespan objective function and incorporate them into the master-problem. We analyze the performance and further enhance the algorithm with two ideas, a Benders optimality cut based on the critical path and a faster heuristic way to solve the sub-problem. 16 standard benchmark instances available in the literature are solved to evaluate and compare the performances of our algorithms with those of the state-of-the-art methods in the literature. The proposed algorithm either results in the optimal solution or improves the best-known solutions in all the existing instances, demonstrating its superiority to the existing state-of-the-art methods in literature.

  Link(s) to publication:

  http://dx.doi.org/10.1016/j.omega.2019.01.003

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