The loss‐averse newsvendor problem with supply options

In this article, we consider a loss‐averse newsvendor with stochastic demand. The newsvendor might procure options when demand is unknown, and decide how many options to execute only after demand is revealed. If the newsvendor reserves too many options, he would incur high reservation costs. Yet reserving too few could result in lost sales. So the newsvendor faces a trade‐off between reservation costs and losing sales. When there are multiple options available, the newsvendor has to consider how many units of each to reserve by studying the trade‐off between flexibility and costs. We show how the newsvendor's loss aversion behavior affects his ordering decision, and propose an efficient algorithm to compute his optimal solution in the general case with n options. We also present examples showing how the newsvendor's ordering strategy changes as loss aversion rises. © 2014 Wiley Periodicals, Inc. 62:46–59, 2015     

Optimal and asymptotically optimal policies for assemble‐to‐order n‐ and W‐systems

We consider two specially structured assemble‐to‐order (ATO) systems—the N‐ and W‐systems—under continuous review, stochastic demand, and nonidentical component replenishment leadtimes. Using a hybrid approach that combines sample‐path analysis, linear programming, and the tower property of conditional expectation, we characterize the optimal component replenishment policy and common‐component allocation rule, present comparative statics of the optimal policy parameters, and show that some commonly used heuristic policies can lead to significant optimality loss. The optimality results require certain symmetry in the cost parameters. In the absence of this symmetry, we show that, for systems with high demand volume, the asymptotically optimal policy has essentially the same structure; otherwise, the optimal policies have no clear structure. For these latter systems, we develop heuristic policies and show their effectiveness. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 62: 617–645, 2015     

Auctions in the post‐change‐order period

A change order is frequently initiated by either the supplier or the buyer, especially when the contract is long‐term or when the contractual design is complex. In response to a change order, the buyer can enter a bargaining process to negotiate a new price. If the bargaining fails, she pays a cancellation fee (or penalty) and opens an auction. We call this process the sequential bargaining‐auction (BA). At the time of bargaining, the buyer is uncertain as to whether the bargained price is set to her advantage; indeed, she might, or might not, obtain a better price in the new auction. To overcome these difficulties, we propose a new change‐order‐handling mechanism by which the buyer has an option to change the contractual supplier after bargaining ends with a bargained price. We call this the option mechanism. By this mechanism, the privilege of selling products or services is transferred to a new supplier if the buyer exercises the option. To exercise the option, the buyer pays a prespecified cash payment, which we call the switch price, to the original supplier. If the option is not exercised, the bargained price remains in effect. When a switch price is proposed by the buyer, the supplier decides whether or not to accept it. If the supplier accepts it, the buyer opens an auction. The option is exercised when there is a winner in the auction. This article shows how, under the option mechanism, the optimal switch price and the optimal reserve price are determined. Compared to the sequential BA, both the buyer and the supplier benefit. Additionally, the option mechanism coordinates the supply chain consisting of the two parties. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 248–265, 2015     

Sojourn times in a two‐stage queueing network with blocking

The model considered in this paper involves a tandem queue consisting of a sequence of two waiting lines. The main feature of our model is blocking, i.e., as soon as the second waiting line reaches a certain upper limit, the first line is blocked. The input of units to the tandem queue is the MAP (Markovian arrival process), and service requirements are of phase type. Our objective is to study the sojourn time distribution under the first‐come‐first‐serve discipline by analyzing the sojourn time through times until absorption in appropriately defined quasi‐birth‐and‐death processes and continuous‐time Markov chains. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Economic ordering decisions with market choice flexibility

Standard approaches to classical inventory control problems treat satisfying a predefined demand level as a constraint. In many practical contexts, however, total demand is comprised of separate demands from different markets or customers. It is not always clear that constraining a producer to satisfy all markets is an optimal approach. Since the inventory‐related cost of an item depends on total demand volume, no clear method exists for determining a market's profitability a priori, based simply on per unit revenue and cost. Moreover, capacity constraints often limit a producer's ability to meet all demands. This paper presents models to address economic ordering decisions when a producer can choose whether to satisfy multiple markets. These models result in a set of nonlinear binary integer programming problems that, in the uncapacitated case, lend themselves to efficient solution due to their special structure. The capacitated versions can be cast as nonlinear knapsack problems, for which we propose a heuristic solution approach that is asymptotically optimal in the number of markets. The models generalize the classical EOQ and EPQ problems and lead to interesting optimization problems with intuitively appealing solution properties and interesting implications for inventory and pricing management. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

Priority queue with customer upgrades

This article is concerned with a general multi‐class multi‐server priority queueing system with customer priority upgrades. The queueing system has various applications in inventory control, call centers operations, and health care management. Through a novel design of Lyapunov functions, and using matrix‐analytic methods, sufficient conditions for the queueing system to be stable or instable are obtained. Bounds on the queue length process are obtained by a sample path method, with the help of an auxiliary queueing system. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Coordinated pricing and inventory control problems with capacity constraints and fixed ordering cost

This article addresses a single‐item, finite‐horizon, periodic‐review coordinated decision model on pricing and inventory control with capacity constraints and fixed ordering cost. Demands in different periods are random and independent of each other, and their distributions depend on the price in the current period. Each period's stochastic demand function is the additive demand model. Pricing and ordering decisions are made at the beginning of each period, and all shortages are backlogged. The objective is to find an optimal policy that maximizes the total expected discounted profit. We show that the profit‐to‐go function is strongly CK‐concave, and the optimal policy has an (s,S,P) ‐like structure. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Optimal production and maintenance policy for imperfect production systems

A joint optimization of the production run length and preventive maintenance (PM) policy is studied for a deteriorating production system where the in‐control period follows a general probability distribution with non‐decreasing failure rate. In the literature, the sufficient conditions for the optimality of the equal‐interval PM schedule is explored to derive an optimal production run length and an optimal number of PM actions. Nevertheless, an exhaustive search may arise. In this study, based on the assumption that the conditions for the optimality of the equal‐interval PM schedule hold, we derive some structural properties for the optimal production/PM policy, which increases the efficiency of the solution procedure. These analyses have implications for the practical application of the production/PM model to be more available in practice. A numerical example of gamma shift distribution with non‐decreasing failure rates is used to illustrate the solution procedure, leading to some insight into the management process. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Bin‐packing problem with concave costs of bin utilization

We consider a generalized one‐dimensional bin‐packing model where the cost of a bin is a nondecreasing concave function of the utilization of the bin. Four popular heuristics from the literature of the classical bin‐packing problem are studied: First Fit (FF), Best Fit (BF), First Fit Decreasing (FFD), and Best Fit Decreasing (BFD). We analyze their worst‐case performances when they are applied to our model. The absolute worst‐case performance ratio of FF and BF is shown to be exactly 2, and that of FFD and BFD is shown to be exactly 1.5. Computational experiments are also conducted to test the performance of these heuristics. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Heart analytics: Analytical modeling of cardiovascular care

Cardiovascular diseases (CVDs) are the leading cause of death and disability both in the United States and worldwide. Despite high morbidity, mortality, and cost in the United States and global healthcare systems, cardiovascular care has been understudied in the healthcare operations management literature. In this paper, we identify research opportunities for healthcare operations management scholars to aid in improving cardiovascular care. We focus on three burdensome conditions, including (1) coronary artery disease, (2) stroke, and (3) heart failure, which, collectively, lead to the vast majority of CVD‐caused mortality and disability. For each condition, we characterize a typical patient's journey in receiving cardiovascular care, elucidating key challenges in improving care and outlining research questions for healthcare operations management scholars. We close with a reference to new research opportunities that emerge as artificial intelligence is likely to transform much of cardiovascular care.