Richard Ivey Building 3340
- Management Consulting
- Data Driven Approaches
- Operations Research
- Incentive Alignment
- Healthcare Operations
- Spreadsheets & VBA
- Process & Flow Analysis
- Project Management
- To search for publications by a specific faculty member, select the database and then select the name from the Author drop down menu.
Professor Mehmet Begen is an industrial engineer and a management scientist with research interests in operations research (OR) applications, healthcare operations management, scheduling, simulation and data-driven approaches.
Besides the Decision Making with Analytics and End User Modeling courses at Ivey, Mehmet has taught courses in optimization and spreadsheet programming in graduate levels at Sauder (UBC).
Mehmet worked in management consulting as a project manager before his Ph.D. studies. He is a Certified Analytics Professional (CAP).”
- Decision Making with Analytics, MBA
- Decision Making with Analytics, HBA
- End User Modeling (Spreadsheet Analytics and VBA), HBA
- Business 9458, Healthcare Analytics (Health Sector), MBA
- Preparatory Knowledge Program, Quantitative Analysis, MBA
- Best Practices: Competing with Analytics, MSc
- Business Project, MSc
- PhD, Management Science - UBC
- MSc, Management Science - UBC
- BSc, Industrial Engineering - METU
Recent Refereed Articles
Lyons, J.; Bell, P. C.; Begen, M. A.,
(Forthcoming), "Solving the Whistler-Blackcomb Mega Day Challenge", Interfaces.
Abstract: The Whistler-Blackcomb (WB) Mega Day Challenge requires a skier to ride all 24 lifts at the resort in a single day. Among over two million skiers annually at WB, only 313 completed the challenge in fourteen months following the introduction of a system that tracks lift use by skier. Apart from the physical challenge, the difficulty is to find a route that matches one’s skill level while accounting for variable lift opening and closing times. brbr We use data from WB’s radio-frequency identification (RFID) ticketing system to estimate ski times between lifts for skiers of various skill levels. We then formulate and solve the problem by a combined, iterative integer programming and heuristic approach, up to the highest feasible skier skill level. The problem’s distinctive features preclude use of known solution methods for similar problems, so we use a practical, staged solution approach. brbr Our results include a recommended route that enables the greatest number of skiers, roughly the fastest quartile, to achieve the challenge. We also provide a benchmark, that skiers who can ski a particular common run in 12 minutes or less, should be able to complete the challenge. In three months following communication of our recommended solution, the rate at which Mega Days were successfully completed increased by two-thirds from the previous seven skiing months.
Habbous,, S.; McArthur, E.; Sarma, S.; Begen, M. A.; Lam, N.; Manns, B.; Lentine, K. L.; Dipchand, C.; Litchfield, K.; Mackenzie, S., et al.,
(Forthcoming), "Potential implications of a more timely living kidney donor evaluation", AMERICAN JOURNAL OF TRANSPLANTATION.
Abstract: Living donor kidney transplantation is the most promising way to avoid or minimize the amount of time a recipient spends on dialysis before transplantation. We studied 887 living kidney donors at five transplant centres in Ontario, Canada who started their evaluation and donated between April 2006 and March 2014. Using a series of hypothetical scenarios, we estimated the impact of an earlier living donor evaluation completion and donation on the number pre-emptive transplants, the time spent on dialysis, healthcare cost savings from averted dialysis costs (CAD $2016), and the number of additional transplants. During the study period, if the donor transplants occurred three months earlier, the healthcare system would save on average $12,055 (standard deviation $13,594) per recipient, 21 recipients could have avoided dialysis altogether, and 57 additional transplants (a 26% increase) could have occurred each year. For the 220 living kidney donor transplants performed in Ontario, Canada each year, this translates to total annual cost savings of $2.7M. In conclusion, a more timely evaluation of living donor candidates and their intended recipients may increase the supply of kidneys for transplantation. Improved evaluation efficiency may also yield more pre-emptive transplants and substantial healthcare cost savings through averted dialysis costs.
Link(s) to publication:
Habbous, S.; McArthur, E.; Dixon, S.; McKenzie, S.; Garcia-Ochoa, C.; Lam, N.; Lentine, K. L.; Dipchand, C.; Litchfield, K.; Begen, M. A., et al.,
(Forthcoming), "Initiating maintenance dialysis prior to living kidney donor transplantation when a donor candidate evaluation is well underway", Transplantation.
Abstract: Introduction: Pre-emptive kidney transplants result in better outcomes and patient experiences than transplantation after dialysis onset. It is unknown how often a person initiates maintenance dialysis prior to living kidney donor transplantation when their donor candidate evaluation is well underway. brbr Methods: Using healthcare databases, we retrospectively studied 478 living donor kidney transplants from 2004-2014 across five transplant centres in Ontario, Canada where the recipients were not receiving dialysis when their donor’s evaluation was well underway. We also explored some factors associated with a higher likelihood of dialysis initiation before transplant.brbr Results: A total 167478 (35%) persons with kidney failure initiated dialysis a median 9.7 (25th-75th percentile 5.4-18.7) months after their donor candidate began their evaluation, and received dialysis for a median 8.8 (3.6-16.9) months before kidney transplantation. The total cohort’s dialysis cost was 8.1 million and 44167 (26%) recipients initiated their dialysis urgently in hospital. The median total donor evaluation time (time from evaluation start to donation) was 10.6 (6.4-21.6) months for pre-emptive transplants and 22.4 (13.1-38.7) months for donors whose recipients started dialysis prior to transplant. Recipients were more likely to start dialysis if their donor was female, non-white, lived in a lower-neighbourhood income, and if the transplant centre received the recipient referral later. brbr Conclusion: One-third of persons initiated dialysis prior to receiving their living kidney donor transplant, despite their donor’s evaluation being well underway. Future studies should consider whether some of these events can be prevented by addressing inappropriate delays to improve patient outcomes and reduce healthcare costs.
Begen, M. A.; Fung, R.; Granot, D.; Granot, F.; Hall, C.; Kluczny , B.,
(Forthcoming), "Evaluation of a Centralized Transportation Assistance System for Passengers with Special Needs at a Canadian Airport", International Journal of Shipping and Transport Logistics.
Abstract: Transportation assistance for travelers with special needs (e.g., disabled, sick, elderly, unaccompanied minors) is provided at most airports around the world, and the demand for this service is increasing every year. At most airports, air carriers are independently responsible for this service, and they set their own service levels and practices. We expect that a centralized system would increase resource efficiency and passenger satisfaction. We conduct an evaluation of such a centralized system at a Canadian airport using two distinct and independent models: simulation and queuing. We find that consolidating the service produces higher levels of service quality for passengers while, at the same time, uses fewer resources. In addition to quantifying the benefits and finding the required resource levels for a given service level, we discuss the pros and cons of a centralized system from the perspectives of the airport authority, the airlines, and the passengers. To the best of our knowledge, this is the first study for consolidating transportation service for special-need passengers. Our methodology may be applied to other airports worldwide to evaluate a centralized transportation assistance system for passengers with special needs.
Habbous,, S.; Sarma, S.; Barnieh, L.; McArthur, E.; Klarenbach, S.; Manns,, B.; Begen, M. A.; Lentine, K. L.; Garg, A. X.,
(Forthcoming), "Health care costs for the evaluation, surgery, and follow-up care of living kidney donors", Transplantation.
Abstract: Background: The health care costs to evaluate, perform surgery, and follow a living kidney donor for the year after donation are poorly described.
Methods: We obtained information on the health care costs of 1099 living kidney donors between April 1, 2004 and March 31, 2014 from Ontario, Canada using comprehensive health care administrative databases. We estimated the cost of three periods of the living donation process: the pre-donation evaluation period (start of evaluation until the day before donation),perioperative period (day of donation until 30-days post-donation), and one year of follow-up period (after perioperative period until 1-year post-donation). We analyzed data for donors and healthy matched non-donor controls using regression-based methods to estimate the incremental cost of living donation. Costs are presented from the perspective of the Canadian health care payer (2017 $CAD).
Results: The incremental health care costs (compared with controls) for the evaluation, perioperative, and follow-up periods were $3,596 (95% confidence interval (CI) $3,350-$3,842), $11,694 ($11,415-$11,973), and $1,011 ($793-$1,230), respectively, totalling $16,290 ($15,814- $16,767). The evaluation cost was higher if the intended recipient started dialysis part-way through the donor evaluation [$886 ($19, $1,752)]. The perioperative cost varied across transplant centres (p<0.0001).
Conclusion: While substantial costs of living donor care are related to the nephrectomy procedure, comprehensive assessment of costs must also include the evaluation and follow-up periods. These estimates are informative for planning future work to support and expand living donation and transplantation, and directing efforts to improve the cost efficiency of living donor care.
Babashov, V.; Aivas, I.; Begen, M. A.; Cao, J. Q.; Rodrigues, G. B.; D'Souza, D.; Lock, M.; Zaric, G. S.,
2017, "Reducing Patient Wait Times for Radiation Therapy and Improving Treatment Planning Process: A Discrete-event Simulation Model", Clinical Oncology, June 29(6): 385 - 391.
Abstract: Background and Purpose We analyzed the radiotherapy planning process at the London Regional Cancer Program (LRCP) to determine the bottlenecks and quantify the impact of specific resource levels with the goal of reducing wait times. Material and Methods We developed a discrete-event simulation (DES) model of a patient’s journey from a point of referral to radiation oncologist to a start of radiotherapy, considering the sequential steps and resources of the treatment planning process. We measured the impact of several resource changes on the ready-to-treat to treatment (RTTT) wait time and on the percent treated within 14-calendar-days target. Results Increasing the number of dosimetrists by one reduced the mean RTTT by 6.55%, leading to 84.92% of patients being treated within the 14-calendar-days target. Adding one more oncologist decreased the mean RTTT from 10.83 to 10.55 days, while a 15% increase in arriving patients increased the wait time by 22.53%. The model was relatively robust to the changes in quantity of other resources. Conclusions Our model identified sensitive and non-sensitive system parameters. A similar approach could be applied by other cancer programs, using their respective data and individualized adjustments, which may be beneficial in making the most effective use of limited resources.
Link(s) to publication:
Ozturk, O.; Begen, M. A.; Zaric, G. S.,
2017, "A branch and bound algorithm for scheduling unit size jobs on parallel batching machines to minimize makespan", International Journal of Production Research, March 55(6): 1815 - 1831.
Abstract: In this paper we present a branch and bound algorithm for the parallel batch scheduling of jobs having different processing times, release dates and unit sizes. There are identical machines with a fixed capacity and the number of jobs in a batch cannot exceed the machine capacity. All batched jobs are processed together and the processing time of a batch is given by the greatest processing time of jobs in that batch. We compare our method to a mixed integer program as well as a method from the literature that is capable of optimally solving instances with a single machine. Computational experiments show that our method is much more efficient than the other two methods in terms of solution time for finding the optimal solution.
Link(s) to publication:
Babashov, V.; Begen, M. A.; Mangel, J.; Zaric, G. S.,
2017, "Economic evaluation of brentuximab vedotin for persistent Hodgkin lymphoma", Current Oncology, March 24(1): e6 - e14.
Abstract: Background: We conducted a cost-effectiveness analysis of brentuximab vedotin (Adcetris) for the treatment of relapsed and refractory Hodgkin lymphoma (HL) in the post-autologous stem cell transplantation (ASCT) failure period, from the perspective of the Canadian health care payer. Methods: We developed a decision-analytical model to simulate lifetime costs and benefits of brentuximab vedotin versus best supportive care for the treatment of HL patients after failure of ASCT. We parameterized the model using administrative data from Ontario, Canada. Results: In the base case, brentuximab vedotin treatment resulted in incremental quality-adjusted life-years (QALYs) of 0.544 and an incremental cost of 89,366 per patient, corresponding to an incremental cost-effectiveness ratio (ICER) of 164,248 per QALY gained. The ICER was sensitive to the cost of brentuximab vedotin, the hazard ratio used to assess the efficacy of brentuximab vedotin treatment, and health state utilities. Conclusions: In light of the available information, brentuximab vedotin has an ICER higher than 100,000 per QALY gained, which is a level often classified as having weak evidence for adoption and appropriate utilization in Canada. However, it is worth noting that provincial cancer agencies take into account not only the costs and associated ICER, but also other factors such as lack of alternative treatment options and clinical benefits of the expensive cancer drugs. Pricing arrangements should be negotiated and risk-sharing agreements or patient access schemes should be explored.
Link(s) to publication:
Caglar Gencosman, B. C.; Begen, M. A.; Ozmutlu, C.; Yilmaz, I. O.,
2016, "Scheduling Methods for Efficient Stamping Operations at an Automotive Company", Production and Operations Management, November 25(11): 1902 - 1918.
Abstract: We consider scheduling issues at Beyçelik, a Turkish automotive stamping company that uses presses to give shape to metal sheets in order to produce auto parts. The problem concerns the minimization of the total completion time of job orders (i.e., makespan) during a planning horizon. This problem may be classified as a combined generalized flowshop and flexible flowshop problem with special characteristics. We show that the Stamping Scheduling Problem is NP-Hard. We develop an integer programming-based method to build realistic and usable schedules. Our results show that the proposed method is able to find higher quality schedules (i.e., shorter makespan values) than both the company's current process and a model from the literature. However, the proposed method has a relatively long run time, which is not practical for the company in situations when a (new) schedule is needed quickly (e.g., when there is a machine breakdown or a rush order). To improve the solution time, we develop a second method that is inspired by decomposition. We show that the second method provides higher-quality solutionsand in most cases optimal solutionsin a shorter time. We compare the performance of all three methods with the company's schedules. The second method finds a solution in minutes compared to Beyçelik's current process, which takes 28 hours. Further, the makespan values of the second method are about 6.1% shorter than the company's schedules. We estimate that the company can save over 187,000 annually by using the second method. We believe that the models and methods developed in this study can be used in similar companies and industries.
Link(s) to publication:
Begen, M. A.; Pun, H.; Yan, X. H.,
2016, "Supply and Demand Uncertainty Reduction Efforts and Cost Comparison", International Journal of Production Economics, October 180: 125 - 134.
Abstract: In industries like health care, consumer goods and agriculture, shortages are widely observed and the consequences can be costly. One of the main drivers of such shortages is the uncertain nature of supply and demand. To reduce uncertainties, sufficient information about supply and demand can be obtained by gathering relevant data (e.g., auditing suppliers and conducting market research). In this paper, we conduct an analysis to examine the impacts of supply uncertainty, demand uncertainty and uncertainty reduction efforts on production quantity and total cost. We show that in the absence of uncertainty reduction efforts, when the financial consequences of shortages are large or when the unit benefit is large, supply uncertainty is more costly than demand uncertainty. In addition, exerting supply uncertainty reduction effort always causes the firm to produce fewer units than exerting demand uncertainty reduction effort. Although supply uncertainty reduction effort delivers a larger degree of improvement to total cost (and hence, is more efficient), reduced supply uncertainty still leads to a higher system cost than does reduced demand uncertainty.
Link(s) to publication:
Ozturk, O.; Begen, M. A.; Zaric, G. S.,
2014, "A branch and bound based heuristic for makespan minimization of washing operations in hospital sterilization services", European Journal of Operational Research, November 239(1): 214 - 226.
Abstract: In this paper, we address the problem of parallel batching of jobs on identical machines to minimize makespan. The problem is motivated from the washing step of hospital sterilization services where jobs have different sizes, different release dates and equal processing times. Machines can process more than one job at the same time as long as the total size of jobs in a batch does not exceed the machine capacity. We present a branch and bound based heuristic method and compare it to a linear model and two other heuristics from the literature. Computational experiments show that our method can find high quality solutions within short computation time.
Link(s) to publication:
Begen, M. A.; Levi, R.; Queyranne, M.,
2012, "A sampling-based approach to appointment scheduling", Operations Research, June 60(3): 675 - 681.
Abstract: We consider the problem of appointment scheduling with discrete random durations, recently studied by Begen and Queyranne (2011), but under the assumption that the duration probability distributions are not known and only a set of independent samples is available, e.g., historical data. For a given sequence of appointments (jobs, tasks), the goal is to determine the planned starting time of each appointment such that the expected total underage and overage costs due to the mismatch between allocated and realized durations is minimized. We use the convexity and subdifferential of the objective function of the appointment scheduling problem to determine bounds on the number of independent samples required to obtain a provably near-optimal solution with high probability.
Link(s) to publication:
Begen, M. A.; Queyranne, M.,
2011, "Appointment Scheduling with Discrete Random Durations", Mathematics of Operations Research, June 36(2): 240 - 257.
Abstract: We consider the problem of determining an optimal appointment schedule for a given sequence of jobs (e.g., medical procedures) on a single processor (e.g., operating room, examination facility, physician), to minimize the expected total underage and overage costs when each job has a random processing duration given by a joint discrete probability distribution. Simple conditions on the cost rates imply that the objective function is submodular and L-convex. Then there exists an optimal appointment schedule which is integer and can be found in polynomial time. Our model can handle a given due date for the total processing (e.g., end of day for an operating room) after which overtime is incurred, and no-shows and some emergencies.
Link(s) to publication:
Santibanez, P.; Begen, M. A.; Atkins, D.,
2007, "Surgical Block Scheduling in a System of Hospitals: An Application to Resource and Wait List Management in a BC Health Authority", Health Care Management Science, October 10(3): 269 - 282.
Abstract: Scheduling surgical specialties in a medical facility is a very complex process. The choice of schedules and resource availability impact directly on the number of patients treated by specialty, cancellations, wait times, and the overall performance of the system. In this paper we present a systemwide model developed to allow management to explore tradeoffs between OR availability, bed capacity, surgeons' booking privileges, and wait lists. We developed a mixed integer programming model to schedule surgical blocks for each specialty into ORs and applied it to the hospitals in a British Columbia Health Authority, considering OR time availability and post-surgical resource constraints. The results offer promising insights into resource optimization and wait list management, showing that without increasing post-surgical resources hospitals could handle more cases by scheduling specialties differently.
Begen, M. A.; Puterman, M. L.,
2003, "Development of a Catch Allocation Tool Design for Production Planning at JS McMillan Fisheries", INFOR, August 41(3): 235 - 244.
Abstract: JS McMillan Fisheries Ltd. (JSM) is a Vancouver-based commercial fishing, production and distribution company. As the operations of JSM evolved, the process of allocating a commercial salmon catch to a set of final products has become complex and time-consuming. We developed a linear programming based decision support tool to assist JSM management with this allocation decision. The decision support tool yields a production plan that maximizes the profit potential of the catch and allows management to carry out "what if" analyses. Moreover, this paper explores implementation issues such as modeling fish quality deterioration, measuring the effect of by-product and addressing catch-size uncertainty.
Honours & Awards
- Second prize for the Informs MSOM Student Paper Competition
- Runner up for the Informs Computing Society Student Paper Competition
- Honorable Mention for the CORS Student Paper Competition
- Honorable Mention for Informs Bonder Scholarship
- CORS Practice Prize
- Informs Case Study Competition Finalist
- Lecturer (MM, MBA and PhD Programs), Sauder School of Business, UBC
- Project Manager and Associate Director, Research, Centre for Operations Excellence, Sauder School of Business, UBC
- Graduate and Teaching Assistant, Sauder School of Business, UBC
- Project Analyst, Centre for Operations Excellence, UBC