Although the impact of layout on the productivity of manufacturing systems is well recognized, a quantification of this impact is an issue that is often ignored or crudely approximated in practice. When evaluating competing layouts for a manufacturing system, the trade-off between their relative benefits and their relative costs underlines the need for a reasonably accurate comparison of the productivity offered by these potential layouts. In this paper, we argue for this approach by comparing the productivity of two well-known layouts in robotic-cell manufacturing: circular and linear. We consider the problem of optimizing throughput in single-gripper, bufferless robotic cells that produce identical parts under the free-pickup criterion and the additive-travel-time metric. For cells with a circular layout, we show that the problem of finding an optimal 1-unit cycle is NP-hard. Our main algorithmic result is a polynomial-time 5/3-approximation algorithm for this problem. We then demonstrate that our algorithm provides near-optimal solutions by compiling its performance on an extensive test bed of practically-relevant instances. Finally, we use the algorithm to assess the increase in throughput for cells with a circular layout over those with a linear layout. We show that a circular layout offers a significant improvement in productivity and demonstrate the robustness of this improvement by examining the sensitivity with respect to changes in the design parameters of the robotic cell. Thus, our work provides operations managers with a tool to trade off the resulting increase in revenue with the additional cost of acquiring and maintaining a robot that can exploit a circular layout.

The goals of the guaranteed support price (GSP) scheme, adopted by several developing countries to support their farmers and the underprivileged population, are threefold: (a) as a supply‐side incentive, to ensure high output from the farmers, (b) as a demand‐side provisioning tool, to subsidize the consumption needs of the poor, and (c) to maintain an adequate amount of foodgrains as reserve stock, to mitigate the adverse effects of yield uncertainty (food security). We offer analytically supported insights on the fundamental aspects of this scheme by analyzing a Stackelberg game between a homogenous population of small farmers and a social planner. We model the strategic behavior of the farmers and the consuming population (Above‐ and Below‐Poverty‐Line consumers), and compare the equilibrium outcome with that under the direct benefit transfer (DBT) scheme, where the social planner simply distributes the budget among the BPL consumers. The comparison of the social planner's surplus depends on the marginal value from maintaining a reserve stock (i.e., the significance of food security). If this value is high, then the surplus under the GSP scheme strictly dominates that under DBT; otherwise, the surplus is identical. The comparison of the production by the farmers depends on two economic forces—the poorness of the BPL consumers and yield uncertainty. If the poorness is extreme, then the two schemes lead to identical production. If yield uncertainty is dominant, then DBT is ineffective in improving production while the GSP scheme can induce a strictly higher production by strategically choosing the reserve stock.

In the automotive industry, many firms source key components from different suppliers, even though the components may function interdependently. In this study, we investigate how component level interdependence impacts quality performance and analyze how various operational factors moderate this relation. We synthesize information from several case studies to model the quality challenges faced by an automotive firm. For several sub‐assemblies that go into its products, the firm sourced key components from two different suppliers. The sub‐assemblies would fail whenever a component fails, but due to interdependent operations, failure of one component could cause the failure of the other. The firm found it challenging to improve the suppliers' quality performance as it was difficult to trace the failures to specific components. Our analysis reveals that – (i) the impact of interdependence is governed by the supply chain structure: reducing the interdependence between components improves quality when suppliers provide the components, but reducing interdependence worsens quality when the firm manufactures the entire sub‐assembly; and (ii) the relation between interdependence and quality performance is moderated by factors such as penalties, production costs, and interdependence costs. Additionally, we find that quality performance is lower when the firm outsources the components than when the firm manufactures the entire sub‐assembly. We identify coordinating mechanisms that leverage incentives and penalties to bridge the quality performance gap.

A dedicated subnetwork (DSN) refers to a subset of lanes, with associated loads, in a shipper's transportation network, for which resources—trucks, drivers, and other equipment—are exclusively assigned to accomplish shipping requirements. The resources assigned to a DSN are not shared with the rest of the shipper's network. Thus, a DSN is an autonomously operated subnetwork and, hence, can be subcontracted. We address a novel problem of extracting a DSN for outsourcing to one or more subcontractors, with the objective of maximizing the shipper's savings. In their pure form, the defining conditions of a DSN are often too restrictive to enable the extraction of a sizable subnetwork. We consider two notions—deadheading and lane‐sharing—that aid in improving the size of the DSN. We show that all the optimization problems involved are both strongly NP‐hard and APX‐hard, and demonstrate several polynomially solvable special cases arising from topological properties of the network and parametric relationships. Next, we develop a network‐flow‐based heuristic that provides near‐optimal solutions to practical instances in reasonable time. Finally, using a test bed based on data obtained from a national 3PL company, we demonstrate the substantial monetary impact of subcontracting a DSN and offer useful managerial insights.

A few weeks before the start of a major season, movie distributors arrange a private screening of the movies to be released during that season for exhibitors and, subsequently, solicit bids for these movies (from exhibitors). Since the number of such solicitations far exceeds the number of movies that can be feasibly screened at a multiplex (i.e., a theater with multiple screens), the problem of interest for an exhibitor is that of choosing a subset of movies for which to submit bids to the distributors. We consider the problem of the selection and screening of movies for a multiplex to maximize the exhibitor's cumulative revenue over a fixed planning horizon. The release times of the movies that can potentially be selected during the planning horizon are known a priori. If selected for screening, a movie must be scheduled through its obligatory period, after which its run may or may not be extended. The problem involves two primary decisions: (i) the selection of a subset of movies for screening from those that can potentially be screened during the planning horizon and (ii) the determination of the duration of screening for the selected movies. We investigate two basic and popular screening policies: preempt-resume and non-preempt. In the preempt-resume policy, the screening of a movie can be preempted and resumed in its post-obligatory period. In the non-preempt policy, a movie is screened continuously from its release time until the time it is permanently withdrawn from the multiplex. We show that optimizing under the preempt-resume policy is strongly NP-hard while the problem under the non-preempt policy is polynomially solvable. We develop efficient algorithms for the problem under both screening policies and show that the revenue obtained from the preempt-resume policy can be significantly higher as compared with that from the non-preempt policy. Our work provides managers of multiplexes with valuable insights into the selection and screening of movies and offers an easy-to-use computational tool to compare the revenues obtainable from adopting these popular policies.