On the design of sparse but efficient structures in operations

It is widely believed that a little flexibility added at the right place can reap significant benefits for operations. Unfortunately, despite the extensive literature on this topic, we are not aware of any general methodology that can be used to guide managers in designing sparse (i.e., slightly flexible) and yet efficient operations. We address this issue using a distributionally robust approach to model the performance of a stochastic system under different process structures. We use the dual prices obtained from a related conic program to guide managers in the design process. This leads to a general solution methodology for the construction of efficient sparse structures for several classes of operational problems. Our approach can be used to design simple yet efficient structures for workforce deployment and for any level of sparsity requirement, to respond to deviations and disruptions in the operational environment. Furthermore, in the case of the classical process flexibility problem, our methodology can recover the k-chain structures that are known to be extremely efficient for this type of problem when the system is balanced and symmetric. We can also obtain the analog of 2-chain for nonsymmetrical system using this methodology. This paper was accepted by Yinyu Ye, optimization. </jats:p

Entry of copycats of luxury brands

We develop a game-theoretic model to examine the entry of copycats and its implications by incorporating two salient features; these features are two product attributes, i.e., physical resemblance and product quality, and two consumer utilities, i.e., consumption utility and status utility. Our equilibrium analysis suggests that copycats with a high physical resemblance but low product quality are more likely to successfully enter the market by defying the deterrence of the incumbent. Furthermore, we show that higher quality can prevent the copycat from successfully entering the market. Finally, we show that the entry of copycats does not always improve consumer surplus and social welfare. In particular, when the quality of the copycat is sufficiently low, the loss in status utility from consumers of the incumbent product overshadows the small gain in consumption utility from buyers of the copycat, leading to an overall decrease in consumer surplus and social welfare. </jats:p

Disruption risk mitigation in supply chains: The risk exposure index revisited

A novel approach has been proposed in the literature using the time-to-recover (TTR) parameters to analyze the risk-exposure index (REI) of supply chains under disruption. This approach is able to capture the cascading effects of disruptions in the supply chains, albeit in simplified environments; TTRs are deterministic, and at most, one node in the supply chain can be disrupted. In this paper, we propose a new method to integrate probabilistic assessment of disruption risks into the REI approach and measure supply chain resiliency by analyzing the worst-case conditional value at risk of total lost sales under disruptions. We show that the optimal strategic inventory positioning strategy in this model can be fully characterized by a conic program. We identify appropriate cuts that can be added to the formulation to ensure zero duality gap in the conic program. In this way, the optimal primal and dual solutions to the conic program can be used to shed light on comparative statics in the supply chain risk mitigation problem. This information can help supply chain risk managers focus their mitigation efforts on critical suppliers and/or installations that will have a greater impact on the performance of the supply chain when disrupted.Accepted versio

Inventory-responsive donor-management policy: A tandem queueing network model

Ministry of Education, Singapore under its Academic Research Funding Tier

Inventory-Responsive Donor-Management Policy:A Tandem Queueing Network Model

Problem definition: In the blood-donor-management problem, the blood bank incentivizes donors to donate, given blood inventory levels. We propose a model to optimize such incentivization schemes under the context of random demand, blood perishability, observation period between donations, and variability in donor arrivals and dropouts. Methodology/results: We propose an optimization model that simultaneously accounts for the dynamics in the blood inventory and the donor’s donation process, as a coupled queueing network. We adopt the Pipeline Queue paradigm, which leads us to a tractable convex reformulation. The coupled setting requires new methodologies to be developed upon the existing Pipeline Queue framework. Numerical results demonstrate the advantages of the optimal policy by comparing it with the commonly adopted and studied threshold policy. Our optimal policy can effectively reduce both shortages and wastage. Managerial implications: Our model is the first to operationalize a dynamic donor-incentivization scheme, by determining the optimal number of donors of different donation responsiveness to receive each type of incentive. It can serve as a decision-support tool that incorporates practical features of blood supply-chain management not addressed thus far, to the best of our knowledge. Simulations on existing policies indicate the dangers of myopic approaches and justify the need for smoother and forward-looking donor-incentivization schedules that can hedge against future demand variation. Our model also has potential wider applications in supply chains with perishable inventory.</p