An approach to the allocation of common costs of multi-mission systems

Many Naval systems, as well as other military and civilian systems, generate multiple missions. An outstanding problem in cost analysis is how to allocate the costs of such missions so that their true costs can be determined and resource allocation optimized. This paper presents a simple approach to handling this problem for single systems. The approach is based on the theory of peak-load pricing as developed by Marcel Boiteux. The basic principle is that the long-run marginal cost of a mission must be equal to its “price.” The implication of this is that if missions can cover their own marginal costs, they should also be allocated some of the marginal common costs. The proportion of costs to be allocated is shown to a function of not only the mission-specific marginal costs and the common marginal costs, but also of the “mission price.” Thus, it is shown that measures of effectiveness must be developed for rational cost allocation. The measurement of effectiveness has long been an intractable problem, however. Therefore, several possible means of getting around this problem are presented in the development of the concept of relative mission prices.     

Flintlock brass fittings from the 19th-century Akko 1 shipwreck,Israel

The Akko 1 shipwreck is the remains of a 26-metre-long Egyptian armed vessel or auxiliary naval brig built at the beginning of the 19th century. Remains of six flintlock muskets were retrieved from the shipwreck, and characterised by various metallurgical methods. The research aimed to study the composition and microstructure of the musket fittings and their manufacturing processes, and if possible, to determine the date and origin of the raw materials. The lead isotope analysis of the fittings suggests that their raw material originated in Great Britain. Based on their typology and composition, the fittings were made in Great Britain of brass alloy and manufactured by casting, probably at the same workshop; and the staple was manufactured by casting and drawing. Considering the zinc content, combined with the manufacturing techniques, the fittings were manufactured between the latter part of the 18th and the early 19th centuries, which might indicate that they were purchased in the course of 19th century weapons trade to be used on board the Egyptian ship.     

Augmented nested sampling for stochastic programs with recourse and endogenous uncertainty

We propose a novel simulation‐based approach for solving two‐stage stochastic programs with recourse and endogenous (decision dependent) uncertainty. The proposed augmented nested sampling approach recasts the stochastic optimization problem as a simulation problem by treating the decision variables as random. The optimal decision is obtained via the mode of the augmented probability model. We illustrate our methodology on a newsvendor problem with stock‐dependent uncertain demand both in single and multi‐item (news‐stand) cases. We provide performance comparisons with Markov chain Monte Carlo and traditional Monte Carlo simulation‐based optimization schemes. Finally, we conclude with directions for future research.     

Resource allocation in an asymmetric technology race with temporary advantages

We consider two opponents that compete in developing asymmetric technologies where each party's technology is aimed at damaging (or neutralizing) the other's technology. The situation we consider is different than the classical problem of commercial R&D races in two ways: First, while in commercial R&D races the competitors compete over the control of market share, in our case the competition is about the effectiveness of technologies with respect to certain capabilities. Second, in contrast with the “winner‐takes‐all” assumption that characterizes much of the literature on this field in the commercial world, we assume that the party that wins the race gains a temporary advantage that expires when the other party develops a superior technology. We formulate a variety of models that apply to a one‐sided situation, where one of the two parties has to determine how much to invest in developing a technology to counter another technology employed by the other party. The decision problems are expressed as (convex) nonlinear optimization problems. We present an application that provides some operational insights regarding optimal resource allocation. We also consider a two‐sided situation and develop a Nash equilibrium solution that sets investment values, so that both parties have no incentive to change their investments. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 59: 128–145, 2012     

Scheduling and lot streaming in two‐machine open shops with no‐wait in process

We study the problem of minimizing the makespan in no‐wait two‐machine open shops producing multiple products using lot streaming. In no‐wait open shop scheduling, sublot sizes are necessarily consistent; i.e., they remain the same over all machines. This intractable problem requires finding sublot sizes, a product sequence for each machine, and a machine sequence for each product. We develop a dynamic programming algorithm to generate all the dominant schedule profiles for each product that are required to formulate the open shop problem as a generalized traveling salesman problem. This problem is equivalent to a classical traveling salesman problem with a pseudopolynomial number of cities. We develop and test a computationally efficient heuristic for the open shop problem. Our results indicate that solutions can quickly be found for two machine open shops with up to 50 products. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Scheduling recurrent construction

A problem we call recurrent construction involves manufacturing large, complex, expensive products such as airplanes, houses, and ships. Customers order configurations of these products well in advance of due dates for delivery. Early delivery may not be permitted. How should the manufacturer determine when to purchase and release materials before fabrication, assembly, and delivery? Major material expenses, significant penalties for deliveries beyond due dates, and long product makespans in recurrent construction motivate choosing a release timetable that maximizes the net present value of cash flows. Our heuristic first projects an initial schedule that dispatches worker teams to tasks for the backlogged products, and then solves a series of maximal closure problems to find material release times that maximize NPV. This method compares favorably with other well‐known work release heuristics in solution quality for large problems over a wide range of operating conditions, including order strength, cost structure, utilization level, batch policy, and uncertainty level. Computation times exhibit near linear growth in problem size. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Predicting intensive care unit bed occupancy for integrated operating room scheduling via neural networks

In a master surgery scheduling (MSS) problem, a hospital's operating room (OR) capacity is assigned to different medical specialties. This task is critical since the risk of assigning too much or too little OR time to a specialty is associated with overtime or deficit hours of the staff, deferral or delay of surgeries, and unsatisfied—or even endangered—patients. Most MSS approaches in the literature focus only on the OR while neglecting the impact on downstream units or reflect a simplified version of the real‐world situation. We present the first prediction model for the integrated OR scheduling problem based on machine learning. Our three‐step approach focuses on the intensive care unit (ICU) and reflects elective and urgent patients, inpatients and outpatients, and all possible paths through the hospital. We provide an empirical evaluation of our method with surgery data for Universitätsklinikum Augsburg, a German tertiary care hospital with 1700 beds. We show that our model outperforms a state‐of‐the‐art model by 43% in number of predicted beds. Our model can be used as supporting tool for hospital managers or incorporated in an optimization model. Eventually, we provide guidance to support hospital managers in scheduling surgeries more efficiently.     

Numerical simulation of warhead transportation

The new numerical approach for analysis of the warhead transportations is suggested.This approach allows to control the warhead operability before its experimental analysis.The approach is implemented by the adequate models for the software ANSYS.Analysis of the loads at land operations and trans-portations of the warhead by natural roads,water and aviation allows to obtain the maximal values of loads,which are used in numerical simulations of the warhead.These loads give an opportunity to analyze the operability and the fatigue strength of the cartridge warhead.The numerical simulations of the attachments of the warhead combat elements are performed on the basis of the suggested method.The data of the numerical simulations verifies the operability of the fastener system of the warhead combat elements.     

Value added analysis for army equipment modernization

This paper describes the Value Added Analysis methodology which is used as part of the U.S. Army's Planning, Programming, Budgeting, and Execution System to assist the Army leadership in evaluating and prioritizing competing weapon system alternatives during the process of building the Army budget. The Value Added Analysis concept uses a family of models to estimate an alternative system's contribution to the Army's effectiveness using a multiattribute value hierarchy. A mathematical optimization model is then used to simultaneously determine an alternative's cost‐benefit and to identify an optimal mix of weapon systems for inclusion in the Army budget. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 233–253, 1999     

An algorithm for optimal shipments with given frequencies

This article deals with the problem of minimizing the transportation and inventory cost associated with the shipment of several products from a source to a destination, when a finite set of shipping frequencies is available. A mixed-integer programming model—shown to be NP-hard—is formulated for that problem. The computational complexity of some similar models applied to different problems is also investigated. In particular, whereas the capacitated plant location problem with operational cost in product form is NP-hard, the simple plant location problem with the same characteristics can be solved in polynomial time. A branch-and-bound algorithm is finally worked out, and some computational results are presented. © 1996 John Wiley & Sons, Inc.