Mustafa (Hayri) Tongarlak

• Ata, B.; Lee, D.; Tongarlak, M. T., (Forthcoming), "A diffusion model of dynamic participant inflow management", Queueing Systems
  Abstract: This paper studies a diffusion control problem motivated by challenges faced by public health agencies who run clinics to serve the public. A key challenge for these agencies is to motivate individuals to participate in the services provided. They must manage the flow of (voluntary) participants so that the clinic capacity is highly utilized, but not overwhelmed. The organization can deploy costly promotion activities to increase the inflow of participants. Ideally, the system manager would like to have enough participants waiting in a queue to serve as many individuals as possible and efficiently use clinic capacity. However, if too many participants sign up, resulting in a long wait, participants may become irritated and hesitate to participate again in future. We develop a diffusion model of managing participant inflow mechanisms. Each mechanism corresponds to choosing a particular drift rate parameter for the diffusion model. The system manager seeks to balance three different costs optimally: (i) a linear holding cost that captures the congestion concerns, (ii) an idleness penalty corresponding to wasted clinic capacity and negative impact on public health, and (iii) costs of promotion activities. We show that a nested-threshold policy for deployment of participant inflow mechanisms is optimal under the long-run average cost criterion. In this policy, the system manager progressively deploys mechanisms in increasing order of cost, as the number of participants in the queue decreases. We derive explicit formulas for the queue length thresholds that trigger each promotion activity, providing the system manager with guidance on when to use each mechanism.

  Link(s) to publication:

  http://dx.doi.org/10.1007/s11134-024-09909-y

• Ata, B.; Tongarlak, M. T.; Lee, D.; Field, J., 2024, "A Dynamic Model for Managing Volunteer Engagement", Operations Research, January 72(5)
  Abstract: Non-profit organizations that provide food, shelter, and other services to people in need, rely on volunteers to deliver their services. Unlike paid labor, non-profit organizations have less control over unpaid volunteers’ schedules, efforts, and reliability. However, these organizations can invest in volunteer engagement activities to ensure a steady and adequate supply of volunteer labor. We study a key operational question of how a non-profit organization can manage its volunteer workforce capacity to ensure consistent provision of services. In particular, we formulate a multiclass queueing network model to characterize the optimal engagement activities for the non-profit organization to minimize the costs of enhancing volunteer engagement, while maximizing productive work done by volunteers. Because this problem appears intractable, we formulate an approximating Brownian control problem in the heavy traffic limit and study the dynamic control of that system. Our solution is a nested threshold policy with explicit congestion thresholds that indicate when the non-profit should optimally pursue various types of volunteer engagement activities. A numerical example calibrated using data from a large food bank shows that our dynamic policy for deploying engagement activities can significantly reduce the food bank's total annual cost of its volunteer operations while still maintaining almost the same level of social impact. This improvement in performance does not require any additional resources -- it only requires that the food bank strategically deploy its engagement activities based on the number of volunteers signed up to work volunteer shifts.

  Link(s) to publication:

  http://dx.doi.org/10.1287/opre.2021.0419

• Ata, B.; Tongarlak, M. T., 2023, "On Scheduling a Multiclass Queue with Abandonments under General Delay Costs", Queueing Systems, May 74: 65 - 104.
  Abstract: We consider a multiclass queueing system with abandonments and general delay costs. A system manager makes dynamic scheduling decisions to minimize long-run average delay and abandonment costs. We consider the three types of delay cost: (i) linear, (ii) convex, and (iii) convex–concave, where the last one corresponds to settings where customers may have a particular deadline in mind but once that deadline passes there is increasingly little difference in the added delay. The dynamic control problem for the queueing system is not tractable analytically. Therefore, we consider the system in the conventional heavy traffic regime and study the approximating Brownian control problem (BCP). We observe that the approximating BCP does not admit a pathwise solution due to abandonments. In particular, the celebrated cμ rule and its extension, the generalized cμ rule, which is asymptotically optimal under convex delay costs with no abandonments, are not optimal in this case. Consequently, we solve the associated Bellman equation, which yields a dynamic index policy (derived from the value function) as the optimal control for the approximating BCP. Interpreting that control in the context of the original queueing system, we propose practical policies for each of the three cases considered and demonstrate their effectiveness through a simulation study.

  Link(s) to publication:

  http://dx.doi.org/10.1007/s11134-012-9326-6

• Lee, D.; Tongarlak, M. T., 2017, "Converting Retail Food Waste into By-Product", European Journal of Operational Research, March 257(3): 944 - 956.
  Abstract: By-product synergy (BPS) is a form of joint production that uses the waste stream from one (primary) process as useful input into another (secondary) process. The synergy is derived from avoiding waste disposal cost in the primary process and virgin raw material cost in the secondary process. BPS increases profit and can have a positive environmental impact by reducing waste. We investigate how BPS can mitigate food waste in a retail grocer setting, and how it interacts with other mechanisms for reducing waste (i.e., waste disposal fee and tax credit for food donation). In the retail setting, waste is generated because of demand uncertainty – the retailer stocks inventory without knowing demand and excess units become waste. We derive the retailer’s optimal order policy under BPS and the order policy for a more practical hybrid implementation of BPS, and compare these BPS implementations to the benchmark case where the retailer only sells fresh produce (“Fresh Only”). We show that the benefit of BPS increases in primary demand uncertainty, but decreases in secondary demand uncertainty. We find that BPS can reduce waste when secondary demand uncertainty and the net tax benefit from donation are low, but can increase waste if increased secondary demand uncertainty drives up safety stock. Our results suggest that under BPS, the threshold net tax benefit required to induce donation increases because BPS competes with donation for excess primary units. We find that the tax credit and disposal fee are substitute mechanisms for inducing food donation.

  Link(s) to publication:

  https://www.sciencedirect.com/science/article/pii/S0377221716306580

  http://dx.doi.org/10.1016/j.ejor.2016.08.022

• Lee, D.; Ata, B.; Tongarlak, M. T., 2017, "Mechanisms for Increasing Sourcing from Capacity-Constrained Local Suppliers", Decision Sciences, February 48(1): 108 - 149.
  Abstract: The fresh produce supply chain is characterized by large (mainstream) farms that are located far from consumers, and capacity‐constrained (local) farms that are located close to the consumer. In this setting, we study: (i) how leadtime and capacity asymmetry between mainstream and local farms affect a retail grocer's order policy for fresh produce, and (ii) how various operational mechanisms can increase the amount sourced from local farms. We show that this supply chain structure is disadvantageous for local suppliers (farms) because it induces the retailer to treat the local supply as a de facto responsive supply without paying a premium for the responsiveness. This disadvantage is exacerbated when the retailer's objective is to achieve a high service level. We study three mechanisms that can improve conditions for local farms: working with an intermediary, backhauling, and a retail order policy, purchase guarantee, that explicitly supports local farms. The intermediary and backhauling mechanisms help the local farm by making local supply more attractive to the retailer, inducing her to order more locally sourced produce. The intermediary reduces the retailer's overstock and stockout costs whereas backhauling increases the average margin. The purchase guarantee order policy helps local farms at the expense of retail profit. However, we show that purchase guarantee and backhauling are complementary mechanisms that together can benefit the retailer and local farms.

  Link(s) to publication:

  http://dx.doi.org/10.1111/deci.12204

• Ata, B.; Lee, D.; Tongarlak, M. T., 2012, "Optimizing Organic Waste to Energy Operations", Manufacturing and Service Operations Management, March 14(2): 231 - 244.
  Abstract: A waste-to-energy firm that recycles organic waste with energy recovery performs two environmentally beneficial functions: it diverts waste from landfills and it produces renewable energy. At the same time, the waste-to-energy firm serves and collects revenue from two types of customers: waste generators who pay for waste disposal service and electricity consumers who buy energy. Given the process characteristics of the waste-to-energy operation, the market characteristics for waste disposal and energy, and the mechanisms regulators use to encourage production of renewable energy, we determine the profit-maximizing operating strategy of the firm. We also show how regulatory mechanisms affect the operating decisions of the waste-to-energy firm. Our analyses suggest that if the social planner's objective is to maximize landfill diversion, offering a subsidy as a per kilowatt-hour for electricity is more cost effective, whereas if the objective is to maximize renewable energy generation, giving a subsidy as a lump sum to offset capital costs is more effective. This has different regulatory implications for urban and rural settings where the environmental objectives may differ.

  Link(s) to publication:

  http://dx.doi.org/10.1287/msom.1110.0359

• Yang, F.; Liu, J.; Nelson, B. L.; Ankenman, B. E.; Tongarlak, M. T., 2011, "Metamodelling for cycle time-throughput-product mix surfaces using progressive model fitting", Production Planning and Control, February 22(1): 50 - 68.
  Abstract: A simulation-based methodology is proposed to map the mean of steady-state cycle time (CT) as a function of throughput (TH) and product mix (PM) for manufacturing systems. Nonlinear regression models motivated by queueing analysis are assumed for the underlying response surface. To ensure efficiency and control estimation error, simulation experiments are built up sequentially using a multi-stage procedure to collect data for fitting the models. The resulting response surface is able to provide a CT estimate for any TH and any PM, and thus allows the decision maker to instantly investigate options and trade offs regarding their production planning.

  Link(s) to publication:

  http://dx.doi.org/10.1080/09537287.2010.490026

• Tongarlak, M. T.; Ankenman, B.; Nelson, B. L.; Borne, L.; Wolfe, K., 2010, "Using Simulation Early in the Design of a Fuel Injector Production Line", Interfaces, March 40(2): 105 - 117.
  Abstract: In this paper, we describe how Delphi Corporation used simulation in the concept-development phase of a new multimillion-dollar fuel injector production line. Delphi wanted to assess the financial viability of production targets and identify the critical features of the line on which it would focus its design-improvement efforts.

  Link(s) to publication:

  https://www.jstor.org/stable/40599432

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