Accuracy assessment of detection performance for sidescan sonars

Sidescan sonars are used in detecting hostile targets on the seabed. An accurate representation of the sensor performance is required to carefully plan and execute searches. We studied several confidence interval methods for assessing the accuracy of detection performance as a function of range from hostile targets. Using simulation, we determined that the best approach for modeling sensor data was piecewise logistic regression with cubic B‐splines at carefully selected knots. This method was demonstrated on real data collected from the CITADEL sea trial. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Implicit enumeration based algorithms for postoptimizing zero-one programs

It has been shown by G. Roodman that useful postoptimization capabilities for the 0-1 integer programming problem can be obtained from an implicit enumeration algorithm modified to classify and collect all fathomed partial solutions. This paper extends the the approach as follows: 1) Improved parameter ranging formulas are obtained by higher resolution classification criteria. 2) Parameters may be changed so as to tighten the original problem, in addition to relaxing it. 3) An efficient storage structure is presented to cope with difficult data collection task implicit in this approach. 4) Finally, computer implementation is facilitated by the elaboration of a unified set of algorithms.     

Cost-based due-date assignment with the use of classical and neural-network approaches

Traditional methods of due-date assignment presented in the literature and used in practice generally assume cost-of-earliness and cost-of-tardiness functions that may bear little resemblance to true costs. For example, practitioners using ordinary least-squares (OLS) regression implicitly minimize a quadratic cost function symmetric about the due date, thereby assigning equal second-order costs to early completion and tardy behavior. In this article the consequences of such assumptions are pointed out, and a cost-based assignment scheme is suggested whereby the cost of early completion may differ in form and/or degree from the cost of tardiness. Two classical approaches (OLS regression and mathematical programming) as well as a neural-network methodology for solving this problem are developed and compared on three hypothetical shops using simulation techniques. It is found for the cases considered that: (a) implicitly ignoring cost-based assignments can be very costly; (b) simpler regression-based rules cited in the literature are very poor cost performers; (c) if the earliness and tardiness cost functions are both linear, linear programming and neural networks are the methodologies of choice; and (d) if the form of the earliness cost function differs from that of the tardiness cost function, neural networks are statistically superior performers. Finally, it is noted that neural networks can be used for a wide range of cost functions, whereas the other methodologies are significantly more restricted. © 1997 John Wiley & Sons, Inc.     

A simple approximation for a multistage capacitated production-inventory system

We develop a simple approximation for multistage production-inventory systems with limited production capacity and variable demands. Each production stage follows a base-stock policy for echelon inventory, constrained by production capacity and the availability of upstream inventory. Our objective is to find base-stock levels that approximately minimize holding and backorder costs. The key step in our procedure approximates the distribution of echelon inventory by a sum of exponentials; the parameters of the exponentials are chosen to match asymptotically exact expressions. The computational requirements of the method are minimal. In a test bed of 72 problems, each with five production stages, the average relative error for our approximate optimization procedure is 1.9%. © 1996 John Wiley & Sons, Inc.     

Brazilian National Defence Policy: foreign policy,national security,economic growth,and technological innovation

ABSTRACT

With the world’s ninth largest economy and comprising nearly 60% of South America’s GDP, 47% of its territory, and 49% of its population, Brazil has become a regional power and an important actor in world affairs over recent decades. This scenario has led the government to re-evaluate its role in the world order, resulting in the enactment of the National Defence Policy, whose objective was to consolidate the country as a regional power while at the same time addressing national security issues, promoting economic development through a series of defence programmes, restructuring the defence industrial base, fostering innovation through technology and knowledge transfer to Brazil, and indigenous research and development. However, the policy’s implementation suffers from several challenges discussed in this article, which may test the capability and competence of Brazilian policymakers, military, industrialists, and other individuals and organisations involved in its implementation.     

Evaluation of base-stock policies in multiechelon inventory systems with state-dependent demands part I: State-independent policies

This article analyzes a model of a multiechelon inventory system. The exogenous demands form Markov-modulated Poisson processes. That is, the demand rates are functions of an underlying Markov chain. Each location follows a base-stock policy which is independent of the state of the underlying Markov chain. We employ the exogenous transit mechanism introduced by Zipkin [7] and Svoronos and Zipkin [6]. The transit times between locations have phase-type distributions. An exact procedure to compute steady-state performance measures is presented. © 1992 John Wiley & Sons, Inc.