Multiple-facility loading under capacity-based economies of scope

Multiple-facility loading (MFL) involves the allocation of products among a set of finite-capacity facilities. Applications of MFL arise naturally in a variety of production scheduling environments. MFL models typically assume that capacity is consumed as a linear function of products assigned to a facility. Product similarities and differences, however, result in capacity-based economies or diseconomies of scope, and thus the effective capacity of the facility is often a (nonlinear) function of the set of tasks assigned to the facility. This article addresses the multiple-facility loading problem under capacity-based economies (and diseconomies) of scope (MFLS). We formulate MFLS as a nonlinear 0–1 mixed-integer programming problem, and we discuss some useful properties. MFLS generalizes many well-known combinatorial optimization problems, such as the capacitated facility location problem and the generalized assignment problem. We also define a tabu-search heuristic and a branch-and-bound algorithm for MFLS. The tabu-search heuristic alternates between two search phases, a regional search and a diversification search, and offers a novel approach to solution diversification. We also report computational experience with the procedures. In addition to demonstrating MFLS problem tractability, the computational results indicate that the heuristic is an effective tool for obtaining high-quality solutions to MFLS. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 229–256, 1997     

Optimizing submarine berthing with a persistence incentive

Submarine berthing plans reserve mooring locations for inbound U.S. Navy nuclear submarines prior to their port entrance. Once in port, submarines may be shifted to different berthing locations to allow them to better receive services they require or to make way for other shifted vessels. However, submarine berth shifting is expensive, labor intensive, and potentially hazardous. This article presents an optimization model for submarine berth planning and demonstrates it with Naval Submarine Base, San Diego. After a berthing plan has been approved and published, changed requests for services, delays, and early arrival of inbound submarines are routine events, requiring frequent revisions. To encourage trust in the planning process, the effect on the solution of revisions in the input is kept small by incorporating a persistence incentive in the optimization model. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 301–318, 1997.     

On the solution of a stochastic bottleneck assignment problem and its variations

In this article, we study the stochastic version of the so-called bottleneck assignment problem. Our primary objective is to maximize the probability that the bottleneck value satisfies a specified target. Under general stochastic assumptions, we show that the solution in this case is easily obtained by solving a linear assignment problem. We next examine the situation where the target is to be minimized, given that the probability of satisfying the target exceeds a specified threshold. Finally, we address extensions to the original problem where a second objective is also considered.     

The reporting time problem: Integration of intelligence with verification

This article is a theoretic study of the following problem in verification: Mobile units under control of an agent, whom we call the HIDER, travel on a known transportation network and must at the conclusion of their itinerary report locations at fixed time intervals to a monitoring authority, whom we call the SEEKER. The purpose of this reporting requirement is to verify that illegal units do not infiltrate the network from sources under the control of the HIDER. We assume that the SEEKER has an independent intelligence-gathering capability which gives sightings of both legal and illegal units. The purpose of this article is to quantify the advantage of frequent over infrequent reporting. © 1992 John Wiley & Sons, Inc.     

Optimal number of minimal repairs before replacement of a system subject to shocks

A system is subject to shocks that arrive according to a nonhomogeneous Poisson process. As shocks occur a system has two types of failures. Type 1 failure (minor failure) is removed by a minimal repair, whereas type 2 failure (catastrophic failure) is removed by replacement. The probability of a type 2 failure is permitted to depend on the number of shocks since the last replacement. A system is replaced at the times of type 2 failure or at the nth type 1 failure, whichever comes first. The optimal policy is to select n* to minimize the expected cost per unit time for an infinite time span. A numerical example is given to illustrate the method. © 1996 John Wiley & Sons, Inc.     

An operational analysis of system calibration

Mathematical models are proposed for studying the impact of miscalibration upon operational effectiveness. Methodology for assessing the system effectiveness and an approach for optimizing the effectiveness of a calibration program are examined. The theory application is discussed and the results of some specific and convenient models are presented.