CON/SLK due date assignment and scheduling on a single machine with two agents

We consider scheduling problems involving two agents (agents A and B), each having a set of jobs that compete for the use of a common machine to process their respective jobs. The due dates of the A‐jobs are decision variables, which are determined by using the common (CON) or slack (SLK) due date assignment methods. Each agent wants to minimize a certain performance criterion depending on the completion times of its jobs only. Under each due date assignment method, the criterion of agent A is always the same, namely an integrated criterion consisting of the due date assignment cost and the weighted number of tardy jobs. Several different criteria are considered for agent B, including the maxima of regular functions (associated with each job), the total (weighted) completion time, and the weighted number of tardy jobs. The overall objective is to minimize the performance criterion of agent A, while keeping the objective value of agent B no greater than a given limit. We analyze the computational complexity, and devise polynomial or pseudo‐polynomial dynamic programming algorithms for the considered problems. We also convert, if viable, any of the devised pseudopolynomial dynamic programming algorithms into a fully polynomial‐time approximation scheme. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 416–429, 2016     

Fully sequential procedures for comparing constrained systems via simulation

We consider the problem of finding the system with the best primary performance measure among a finite number of simulated systems in the presence of a stochastic constraint on a single real‐valued secondary performance measure. Solving this problem requires the identification and removal from consideration of infeasible systems (Phase I) and of systems whose primary performance measure is dominated by that of other feasible systems (Phase II). We use indifference zones in both phases and consider two approaches, namely, carrying out Phases I and II sequentially and carrying out Phases I and II simultaneously, and we provide specific example procedures of each type. We present theoretical results guaranteeing that our approaches (general and specific, sequential and simultaneous) yield the best system with at least a prespecified probability, and we provide a portion of an extensive numerical study aimed at evaluating and comparing the performance of our approaches. The experimental results show that both new procedures are useful for constrained ranking and selection, with neither procedure showing uniform superiority over the other.© 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

On the polyhedral structure of two‐level lot‐sizing problems with supplier selection

In this article, we study a two‐level lot‐sizing problem with supplier selection (LSS), which is an NP‐hard problem arising in different production planning and supply chain management applications. After presenting various formulations for LSS, and computationally comparing their strengths, we explore the polyhedral structure of one of these formulations. For this formulation, we derive several families of strong valid inequalities, and provide conditions under which they are facet‐defining. We show numerically that incorporating these valid inequalities within a branch‐and‐cut framework leads to significant improvements in computation. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 647–666, 2017     

Counterinsurgency as armed reform: The political history of the Malayan Emergency

Despite the emphasis in doctrine and academia that counterinsurgency is in its essence political, these operations are all too commonly discussed and approached as primarily military endeavors. Informed by the need to refocus counterinsurgency studies, this article revisits a foundational case of the canon – the Malayan Emergency – to discuss its political (i.e., not military) unfolding. The analysis distinguishes itself by emphasizing the diplomatic processes, negotiations, and deals that gave strategic meaning to the military operations underway. In so doing, the article also generates insight on the use of leverage and elite bargains in creating new political settlements and bringing insurgent conflicts to an end.     

Retailer's rationale to refuse consumer returns in supply chains

While accepting consumer returns has long been proposed as a solution to resolve the consumer valuation uncertainty problem, there are still a sizable portion of retailers who insist on a “no return” policy. In this article, we offer an economic rationale for these seemingly unreasonable strategies in a supply chain context. We demonstrate when and why the retailer may benefit from refusing consumer returns, even though offering consumer returns allows the supply chain to implement the expostmarket segmentation. Granting the retailer the right to refuse consumer returns may sometimes improve supply chain efficiency: it eliminates the manufacturer's attempt to induce inefficient consumer returns and bring the equilibrium back to that in the vertically integrated benchmark. We also find that the refund and the retail price can move in the opposite directions when product reliability varies, and consumer returns have a nontrivial impact on the quality choice. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 686–701, 2015     

Balancing stability and efficiency in team formation as a generalized roommate problem

The assignment of personnel to teams is a fundamental managerial function typically involving several objectives and a variety of idiosyncratic practical constraints. Despite the prevalence of this task in practice, the process is seldom approached as an optimization problem over the reported preferences of all agents. This is due in part to the underlying computational complexity that occurs when intra-team interpersonal interactions are taken into consideration, and also due to game-theoretic considerations, when those taking part in the process are self-interested agents. Variants of this fundamental decision problem arise in a number of settings, including, for example, human resources and project management, military platooning, ride sharing, data clustering, and in assigning students to group projects. In this article, we study an analytical approach to “team formation” focused on the interplay between two of the most common objectives considered in the related literature: economic efficiency (i.e., the maximization of social welfare) and game-theoretic stability (e.g., finding a core solution when one exists). With a weighted objective across these two goals, the problem is modeled as a bi-level binary optimization problem, and transformed into a single-level, exponentially sized binary integer program. We then devise a branch-cut-and-price algorithm and demonstrate its efficacy through an extensive set of simulations, with favorable comparisons to other algorithms from the literature.     

The Production and Deposition of the Guisborough Helmet

In September 1878 the British Museum received a donation of a folded metal plate which had been embossed and gilded. Restoration of the object revealed that the folded plate was in fact the outer casing of a Roman copper alloy cavalry sports type helmet which dates to the late second or third century AD. The story of what became known as the Guisborough helmet began 14 years earlier in what was then the North Riding of Yorkshire when workers employed by the Cleveland Railway Company discovered a ‘very curious plate of metal’ during road construction. It appears that the helmet was deliberately prepared for deposition and buried at a depth of c30 cm close to a stream. Examination by the authors suggests that this was a high value item that had been repaired many times. Experimental evidence suggests that the decoration alone required approximately 16 h to fashion.     

Impact of reseller's and sales agent's forecasting accuracy in a multilayer supply chain

We consider a three‐layer supply chain with a manufacturer, a reseller, and a sales agent. The demand is stochastically determined by the random market condition and the sales agent's private effort level. Although the manufacturer is uninformed about the market condition, the reseller and the sales agent conduct demand forecasting and generate private demand signals. Under this framework with two levels of adverse selection intertwined with moral hazard, we study the impact of the reseller's and the sales agent's forecasting accuracy on the profitability of each member. We show that the manufacturer's profitability is convex on the reseller's forecasting accuracy. From the manufacturer's perspective, typically improving the reseller's accuracy is detrimental when the accuracy is low but is beneficial when it is high. We identify the concrete interrelation among the manufacturer‐optimal reseller's accuracy, the volatility of the market condition, and the sales agent's accuracy. Finally, the manufacturer's interest may be aligned with the reseller's when only the reseller can choose her accuracy; this alignment is never possible when both downstream players have the discretion to choose their accuracy. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 207–222, 2014     

Return policy: Hassle‐free or your money‐back guarantee?

This article compares the profitability of two pervasively adopted return policies—money‐back guarantee and hassle‐free policies. In our model, a seller sells to consumers with heterogeneous valuations and hassle costs. Products are subject to quality risk, and product misfit can only be observed post‐purchase. While the hassle‐free policy is cost advantageous from the seller's viewpoint, a money‐back guarantee allows the seller to fine‐tune the consumer hassle on returning the product. Thus, when the two return policies lead to the same consumer behaviors, the hassle‐free policy dominates. Conversely, a money‐back guarantee can be more profitable even if on average, high‐valuation consumers experience a lower hassle cost than the low‐valuation ones. The optimal hassle cost can be higher when product quality gets improved; thus, it is not necessarily a perfect proxy or signal of the seller's quality. We further allow the seller to adopt a mixture of these policies, and identify the concrete operating regimes within which these return policies are optimal among more flexible policies. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 403–417, 2014