When is greedy module assembly optimal?

Many coherent systems are configurations of identically structured modules, each consisting of a number of different components. The objective is to assemble the modules out of a collection of available components, and to install the modules in the system in a way that maximizes reliability. The greedy assembly rule builds one module out of the best available components, another out of the best remaining components, and so on. This article shows that greedy assembly is optimal whenever the modules have a series structure, no matter what the structure of the system in which the modules will be used might be, provided that the modules, once assembled, are installed in the system in an optimal way. The article also demonstrates that series modules are unique in this regard.     

Optimizing the allocation of components to kits in small-lot,multiechelon assembly systems

The kitting problem in multiechelon assembly systems is to allocate on-hand stock and anticipated future deliveries to kits so that cost is minimized. This article structures the kitting problem and describes several preprocessing methods that are effective in refining the formulation. The model is resolved using an optimizing approach based on Lagrangian relaxation, which yields a separable problem that decomposes into a subproblem for each job. The resulting subproblems are resolved using a specialized dynamic programming algorithm, and computational efficiency is enhanced by dominance properties devised for that purpose. The Lagrangian problem is resolved effectively using subgradient optimization and a specialized branching method incorporated in the branch-and-bound procedure. Computational experience demonstrates that the specialized approach outperforms the general-purpose optimizer OSL. The new solution approach facilitates time-managed flow control, prescribing kitting decisions that promote cost-effective performance to schedule. © 1994 John Wiley & Sons. Inc.     

The frequency assignment problem: A solution via nonlinear programming

This paper gives a mathematical programming model for the problem of assigning frequencies to nodes in a communications network. The objective is to select a frequency assignment which minimizes both cochannel and adjacent-channel interference. In addition, a design engineer has the option to designate key links in which the avoidance of jamming due to self interference is given a higher priority. The model has a nonconvex quadratic objective function, generalized upper-bounding constraints, and binary decision variables. We developed a special heuristic algorithm and software for this model and tested it on five test problems which were modifications of a real-world problem. Even though most of the test problems had over 600 binary variables, we were able to obtain a near optimum in less than 12 seconds of CPU time on a CDC Cyber-875.     

The complementary use of regression diagnostics and robust estimators

Regression modeling for prediction or forecasting purposes is critically dependent on the quality of the data which are used to estimate the model parameters. Extreme response or predictor-variable values can substantially influence least-squares estimates and disproportionately affect predictions. Robust alternatives to least-squares are less sensitive to extreme observations and can provide more precise predictions. In this article diagnostic displays are used to identify extreme observations and to assess the sensitivity of least-squares parameter estimates and predictions to the inclusion of these observations in a data set. The displays are shown to aid in the interpretation of weights which robust estimators assign to influential observations.     

An extremal problem in subconnectivity

The connectivity of a subgraph of a graph can exceed the connectivity of the graph. We call the largest of the connectivities of all subgraphs the subconnectivity. We then give the exact solution to the extremal problem of determining the maximum number of lines in a p-point graph of subconnectivity two.     

Building the Rule of Law: A Model of Police-Military Relations in Latin America

United States policy makers and academic researchers have neglected the deep institutional rivalries between police agencies and military services in Latin America. The problems of police/military coordination have complicated US national goals of democratization, strengthening the rule of law and combating the production and trafficking of illicit drugs in the region. Police agencies stand at the epicenter of dysfunctional criminal justice systems. Although the US policy of engagement with Latin American military services is intended to reorient their roles and missions towards supporting democratically elected civilian governments, US counternarcotics assistance programs have encouraged a wider Latin American military role in drug interdiction. This article develops an analytical model to identify the dimensions of police-military conflict in the context of the fundamental reform of criminal justice systems in Latin America.     

The value of information sharing in a two‐stage supply chain with production capacity constraints

We consider a simple two‐stage supply chain with a single retailer facing i.i.d. demand and a single manufacturer with finite production capacity. We analyze the value of information sharing between the retailer and the manufacturer over a finite time horizon. In our model, the manufacturer receives demand information from the retailer even during time periods in which the retailer does not order. To analyze the impact of information sharing, we consider the following three strategies: (1) the retailer does not share demand information with the manufacturer; (2) the retailer does share demand information with the manufacturer and the manufacturer uses the optimal policy to schedule production; (3) the retailer shares demand information with the manufacturer and the manufacturer uses a greedy policy to schedule production. These strategies allow us to study the impact of information sharing on the manufacturer as a function of the production capacity, and the frequency and timing in which demand information is shared. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

Approximation algorithms for general one‐warehouse multi‐retailer systems

Logistical planning problems are complicated in practice because planners have to deal with the challenges of demand planning and supply replenishment, while taking into account the issues of (i) inventory perishability and storage charges, (ii) management of backlog and/or lost sales, and (iii) cost saving opportunities due to economies of scale in order replenishment and transportation. It is therefore not surprising that many logistical planning problems are computationally difficult, and finding a good solution to these problems necessitates the development of many ad hoc algorithmic procedures to address various features of the planning problems. In this article, we identify simple conditions and structural properties associated with these logistical planning problems in which the warehouse is managed as a cross‐docking facility. Despite the nonlinear cost structures in the problems, we show that a solution that is within ε‐optimality can be obtained by solving a related piece‐wise linear concave cost multi‐commodity network flow problem. An immediate consequence of this result is that certain classes of logistical planning problems can be approximated by a factor of (1 + ε) in polynomial time. This significantly improves upon the results found in literature for these classes of problems. We also show that the piece‐wise linear concave cost network flow problem can be approximated to within a logarithmic factor via a large scale linear programming relaxation. We use polymatroidal constraints to capture the piece‐wise concavity feature of the cost functions. This gives rise to a unified and generic LP‐based approach for a large class of complicated logistical planning problems. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009