Determination of efficient points in multiple-objective location problems

This article is devoted to an MCDM problem connected with locational analysis. The MCDM problem can be formulated so as to minimize the distance between a facility and a given set of points. The efficient points of this problem are candidates for optimal solutions to many location problems. We propose an algorithm to find all efficient points when distance is measured by any polyhedral norm.     

Precision cyber weapon systems: An important component of a responsible national security strategy?

Given the advances made in conventional weapon capabilities, precision should by now be the accepted and expected norm in cyberspace as well. In this article I argue that developing precision cyber weapon systems, to be used during a lawful conflict, can be an important part of a responsible national security strategy to reduce the amount of violence and physical destruction in conflicts. I first describe a precision cyber weapon system in a military context. I then present three compelling rationales for the development of precision cyber weapon systems based on ethical, operational, and financial considerations. To support the position, I address several arguments that have been levied against their development. Thereafter I present several recommendations for a way ahead.     

Technical note: A computationally efficient algorithm for undiscounted Markov decision processes with restricted observations

We present a computationally efficient procedure to determine control policies for an infinite horizon Markov Decision process with restricted observations. The optimal policy for the system with restricted observations is a function of the observation process and not the unobservable states of the system. Thus, the policy is stationary with respect to the partitioned state space. The algorithm we propose addresses the undiscounted average cost case. The algorithm combines a local search with a modified version of Howard's (Dynamic programming and Markov processes, MIT Press, Cambridge, MA, 1960) policy iteration method. We demonstrate empirically that the algorithm finds the optimal deterministic policy for over 96% of the problem instances generated. For large scale problem instances, we demonstrate that the average cost associated with the local optimal policy is lower than the average cost associated with an integer rounded policy produced by the algorithm of Serin and Kulkarni Math Methods Oper Res 61 (2005) 311–328. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2009     

Diffusion approximation to the G/G/R machine repair problem with warm standby spares

The G/G/R machine repair problem with M operating machines, S warm standby spares, and R repairmen is studied as a diffusion process. The steady-state equations are formulated as diffusion equations subject to two reflecting barriers. The approximate diffusion parameters of the diffusion equations are obtained (1) under the assumption that the input characteristics of the problem are defined only by their first two moments rather than their probability distribution function, (2) under the assumption of heavy traffic approximation, that is, when queues of failed machines in the repair stage are almost always nonempty, and (3) using well-known asymptotic results from renewal theory. Expressions for the probability density functions of the number of failed machines in the system are obtained. A study of the derived approximate results, compared to some of the exact results, suggests that the diffusion approach provides a useful method for solving complex machine-repair problems.     

Optimal force mix in heterogeneous combat

This article presents models for determining the optimum number of Red weapons required to win a heterogeneous combat in which m(m> 1) types of Red weapons face a single type of Blue weapon under a newly defined termination policy. Red aims at either minimizing the total cost or maximizing the aggregated remaining force strength. Kuhn-Tucker and simulated annealing techniques are used for obtaining the optimal solution. The methodology is illustrated by analysing heterogeneous combat to determine (i) the feasibility of introducing new types of weapons and (ii) the number of weapons required to win if a specific type of weapon, say infantry, dominates. © 1995 John Wiley & Sons, Inc.     

Note on “An Optimal Recursive Method for Various Inventory Replenishment Models with Increasing Demand and Shortages” by Teng et al.

In a recent paper, Teng, Chern, and Yang consider four possible inventory replenishment models and determine the optimal replenishment policies for them. They compare these models to identify the best alternative on the basis of minimum total relevant inventory costs. The total cost functions for Model 1 and Model 4 as derived by them are not exact for the comparison. As a result, their conclusion on the least expensive replenishment policy is incorrect. The present article provides the actual total costs for Model 1 and Model 4 to make a correct comparison of the four models. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 602–606, 2000     

Analysis of project scheduling strategies in a client-contractor environment

In this article we consider a cost-minimization model to investigate scheduling strategies for multistaged projects in a client-contractor environment. This type of environment is symptomatic of temporal changes in project definition and scope. At prespecified epochs the client conducts an external evaluation of the project and either accepts or rejects the contractor's current work. The resulting uncertainty from the client's review is modeled via monotonically varying acceptance probabilities. The model is designed primarily to address the interaction between earliest-, intermediate-, and latest-start options and project-crashing stragies for a broad range of penalty costs. Theoretical results are introduced, while numerical examples for both exponentially and polynomially based acceptance probabilities are discussed.     

Exploiting self‐canceling demand point aggregation error for some planar rectilinear median location problems

When solving location problems in practice it is quite common to aggregate demand points into centroids. Solving a location problem with aggregated demand data is computationally easier, but the aggregation process introduces error. We develop theory and algorithms for certain types of centroid aggregations for rectilinear 1‐median problems. The objective is to construct an aggregation that minimizes the maximum aggregation error. We focus on row‐column aggregations, and make use of aggregation results for 1‐median problems on the line to do aggregation for 1‐median problems in the plane. The aggregations developed for the 1‐median problem are then used to construct approximate n‐median problems. We test the theory computationally on n‐median problems (n ≥ 1) using both randomly generated, as well as real, data. Every error measure we consider can be well approximated by some power function in the number of aggregate demand points. Each such function exhibits decreasing returns to scale. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 614–637, 2003.     

‘A Brave New World for Chinese Joint Operations’

A key organizational challenge for all modern militaries is instituting an effective command-and-control (C2) structure for joint operations. China has been a relative latecomer to joint operations, with a persistent weakness in joint C2. Reforms launched in early 2016 sought to overcome this challenge by establishing a permanent two-level joint C2 structure. Although not a ‘tipping point’ that will lead ineluctably to stronger operational effectiveness, this reform is nonetheless an important milestone in an evolutionary process towards better PLA joint operations. The result could be added operational challenges for several of China’s neighbors and the United States.