Capacity improvement,penalties, and the fixed charge transportation problem

Capacity improvement and conditional penalties are two computational aides for fathoming subproblems in a branch‐and‐bound procedure. In this paper, we apply these techniques to the fixed charge transportation problem (FCTP) and show how relaxations of the FCTP subproblems can be posed as concave minimization problems (rather than LP relaxations). Using the concave relaxations, we propose a new conditional penalty and three new types of capacity improvement techniques for the FCTP. Based on computational experiments using a standard set of FCTP test problems, the new capacity improvement and penalty techniques are responsible for a three‐fold reduction in the CPU time for the branch‐and‐bound algorithm and nearly a tenfold reduction in the number of subproblems that need to be evaluated in the branch‐and‐bound enumeration tree. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 341–355, 1999     

On the use of lexicographic min cost flows in evacuation modeling

Building evacuation problems can be represented as dynamic network-flow problems [3]. The underlying network structure of a building evolves through time yielding a time-expanded network (a dynamic network). Usually in such evacuation problems involving time, more than one objective function is appropriate. For example, minimizing the total evacuation time and evacuating a portion of the building as early as possible are two such objectives. In this article we show that lexicographical optimization is applicable in handling such multiple objectives. Minimizing the total evacuation time while avoiding cyclic movements in a building and “priority evacuation” are treated as lexicographical min cost flow problems.     

Inventory rotation policies for slow moving items

In this article we present a stochastic model for determining inventory rotation policies for a retail firm which must stock many hundreds of distinctive items having uncertain heterogeneous sales patterns. The model develops explicit decision rules for determining (1) the length of time that an item should remain in inventory before the decision is made on whether or not to rotate the item out of inventory and (2) the minimum sales level necessary for retaining the item in inventory. Two inventory rotation policies are developed, the first of which maximizes cumulative expected sales over a finite planning horizon and the second of which maximizes cumulative expected profit. We also consider the statistical behavior of items having uncertain, discrete, and heterogeneous sales patterns using a two-period prediction methodology where period 1 is used to accumulate information on individual sales rates and this knowledge is then used, in a Bayesian context, to make sales predictions for period 2. This methodology assumes that over an arbitrary time interval sales for each item are Poisson with unknown but stationary mean sales rates and the mean sales rates are distributed gamma across all items. We also report the application of the model to a retail firm which stocks many hundreds of distinctive unframed poster art titles. The application provides some useful insights into the behavior of the model as well as some interesting aspects pertaining to the implementation of the results in a “real-world” situation.     

An optimal critical level policy for inventory systems with two demand classes

Traditional inventory systems treat all demands of a given item equally. This approach is optimal if the penalty costs of all customers are the same, but it is not optimal if the penalty costs are different for different customer classes. Then, demands of customers with high penalty costs must be filled before demands of customers with low penalty costs. A commonly used inventory policy for dealing with demands with different penalty costs is the critical level inventory policy. Under this policy demands with low penalty costs are filled as long as inventory is above a certain critical level. If the inventory reaches the critical level, only demands with high penalty costs are filled and demands with low penalty costs are backordered. In this article, we consider a critical level policy for a periodic review inventory system with two demand classes. Because traditional approaches cannot be used to find the optimal parameters of the policy, we use a multidimensional Markov chain to model the inventory system. We use a sample path approach to prove several properties of this inventory system. Although the cost function is not convex, we can build on these properties to develop an optimization approach that finds the optimal solution. We also present some numerical results. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Tests for transient means in simulated time series

We present a family of tests to detect the presence of a transient mean in a simulation process. These tests compare variance estimators from different parts of a simulation run, and are based on the methods of batch means and standardized time series. Our tests can be viewed as natural generalizations of some previously published work. We also include a power analysis of the new tests, as well as some illustrative examples. © 1994 John Wiley & Sons, Inc.     

A simulated annealing approach to the cyclic staff-scheduling problem

This article presents the application of a simulated annealing heuristic to an NP-complete cyclic staff-scheduling problem. The new heuristic is compared to branch-and-bound integer programming algorithms, as well as construction and linear programming-based heuristics. It is designed for use in a continuously operating scheduling environment with the objective of minimizing the number of employees necessary to satisfy forecast demand. The results indicate that the simulated annealing-based method tends to dominate the branch-and-bound algorithms and the other heuristics in terms of solution quality. Moreover, the annealing algorithm exhibited rapid convergence to a low-cost solution. The simulated annealing heuristic is executed in a single program and does not require mathematical programming software. © 1993 John Wiley & Sons, Inc.     

Note: A local-search heuristic for large set-covering problems

In this note we describe a local-search heuristic (LSH) for large non-unicost set-covering problems (SCPs). The new heuristic is based on the simulated annealing algorithm and uses an improvement routine designed to provide low-cost solutions within a reasonable amount of CPU time. The solution costs associated with the LSH compared very favorably to the best previously published solution costs for 20 large SCPs taken from the literature. In particular, the LSH yielded new benchmark solutions for 17 of the 20 test problems. We also report that, for SCPs where column cost is correlated with column coverage, the new heuristic provides solution costs competitive with previously published results for comparable problems. © 1995 John Wiley & Sons, Inc.     

Use of a classifier in a knowledge-based simulation optimization system

This article defines and develops a simulation optimization system based upon response surface classification and the integration of multiple search strategies. Response surfaces are classified according to characteristics that indicate which search technique will be most successful. Typical surface characteristics include statistical measures and topological features, while search techniques encompass response surface methodology, simulated annealing, random search, etc. The classify-then-search process flow and a knowledge-based architecture are developed and then demonstrated with a detailed computer example. The system is useful not only as an approach to optimizing simulations, but also as a means for integrating search techniques and thereby providing the user with the most promising path toward an optimal solution. © 1995 John Wiley & Sons, Inc.     

Present practices and future plans for MIL-STD-781

MIL-STD-781 specifies reliability acceptance test procedures based on both fixed-length tests and probability ratio sequential tests. The assumption underlying MIL-STD-781 is a constant mean time between failures (MTBF) and typical practice applies MIL-STD-781 to electrical, electronic, and mechanical equipment. This article discusses some of the difficulties that have prompted the C and D revisions of MIL-STD-781. In addition, it discusses the relationship of MIL-STD-781 with MIL-STD-1635(EC) which deals with reliability growth testing. The article concludes with a discussion of needed research in reliability growth testing, in support of MIL-STD-781, and in the area of stress and its impact of MTBF.     

An application of empirical bayes techniques to the simultaneous estimation of many probabilities

Consider the following situation: Each of N different combat units is presented with a number of requirements to satisfy, each requirement being classified into one of K mutually exclusive categories. For each unit and each category, an estimate of the probability of that unit satisfying any requirement in that category is desired. The problem can be generally stated as that of estimating N different K-dimensional vectors of probabilities based upon a corresponding set of K-dimensional vectors of sample proportions. An empirical Bayes model is formulated and applied to an example from the Marine Corps Combat Readiness Evaluation System (MCCRES). The EM algorithm provides a convenient method of estimating the prior parameters. The Bayes estimates are compared to the ordinary estimates, i.e., the sample proportions, by means of cross validation, and the Bayes estimates are shown to provide considerable improvement.