The discrete evasion game with three-move lag

The discrete evasion game with three-move lag, formulated over 30 years ago, was one of the earliest games with time-lag complications. This game remains unsolved even though it is well known that the game has a value. In this article we obtain an upper bound for the value by constructing a strategy which consists of 400 conditional probabilities for the minimizing player. This is believed to be the best upper bound known.     

On the robustness of the modified beta distribution for acceptance sampling in statistical quality control

The purpose of this article is to examine the robustness of the modified Beta distribution as a probability distribution of lot fraction defectives in Bayesian acceptance sampling for statistical quality control. In complex manufacturing systems, a production process may consist of multiple production stages in a serial or nonserial fashion. Hence, inputs to a production station can be a result of subassembly of several inputs, or outputs of some inspection stations for some prior work stages. We investigate the effectiveness of the modified Beta distribution as an approximation to the lot fraction defectives probability of inputs at intermediate work stations. The robustness of the modified Beta distribution simplifies both the determination of the optimal sampling plan for acceptance sampling, and the calibration of distributions resulted from subassembly or inspection operations in complex manufacturing systems.     

Approximate semieconomic design of control charts with multiple control limtis

Statistical quality control of complicated production processes subject to a multiplicity of assignable causes may require the utilization of control charts with multiple control limits. This article presents an approximate semieconomic design of such charts, which is easily implementable in practical situations. Evaluations of the semieconomic control chart design show that the proposed approximate method results in solutions that are very close to the true optima and can be obtained with minimal computational effort.     

Discrete repairable reliability systems

Consider a reliability system consisting of n components. The failures and the repair completions of the components can occur only at positive integer-valued times k ϵ N₊₊ ϵ (1, 2, …). At any time k ϵ N₊₊ each component can be in one of two states: up (i.e., working) or down (i.e., failed and in repair). The system state is also either up or down and it depends on the states of the components through a coherent structure function τ. In this article we formulate mathematically the above model and we derive some of its properties. In particular, we identify conditions under which the first failure times of two such systems can be stochastically ordered. A variety of special cases is used in order to illustrate the applications of the derived properties of the model. Some instances in which the times of first failure have the NBU (new better than used) property are pointed out. © 1993 John Wiley & Sons, Inc.     

Scheduling semiconductor test operations: Minimizing maximum lateness and number of tardy jobs on a single machine

We examine a class of single-machine scheduling problems with sequence-dependent setup times that arise in the context of semiconductor test operations. We present heuristics for the problems of minimizing maximum lateness with dynamic arrivals and minimizing number of tardy jobs. We exploit special problem structure to derive worst-case error bounds. The special problem structure also enables us to derive dynamic programming procedures for the problems where all jobs are available simultaneously.     

Multi-item service constrained (s,S) policies for spare parts logistics systems

Many organizations providing service support for products or families of products must allocate inventory investment among the parts (or, identically, items) that make up those products or families. The allocation decision is crucial in today's competitive environment in which rapid response and low levels of inventory are both required for providing competitive levels of customer service in marketing a firm's products. This is particularly important in high-tech industries, such as computers, military equipment, and consumer appliances. Such rapid response typically implies regional and local distribution points for final products and for spare parts for repairs. In this article we fix attention on a given product or product family at a single location. This single-location problem is the basic building block of multi-echelon inventory systems based on level-by-level decomposition, and our modeling approach is developed with this application in mind. The product consists of field-replaceable units (i.e., parts), which are to be stocked as spares for field service repair. We assume that each part will be stocked at each location according to an (s, S) stocking policy. Moreover, we distinguish two classes of demand at each location: customer (or emergency) demand and normal replenishment demand from lower levels in the multiechelon system. The basic problem of interest is to determine the appropriate policies (s_i S_i) for each part i in the product under consideration. We formulate an approximate cost function and service level constraint, and we present a greedy heuristic algorithm for solving the resulting approximate constrained optimization problem. We present experimental results showing that the heuristics developed have good cost performance relative to optimal. We also discuss extensions to the multiproduct component commonality problem.     

Scheduling maintenance and semiresumable jobs on a single machine

The majority of scheduling literature assumes that the machines are available at all times. In this paper, we study single machine scheduling problems where the machine maintenance must be performed within certain intervals and hence the machine is not available during the maintenance periods. We also assume that if a job is not processed to completion before the machine is stopped for maintenance, an additional setup is necessary when the processing is resumed. Our purpose is to schedule the maintenance and jobs to minimize some performance measures. The objective functions that we consider are minimizing the total weighted job completion times and minimizing the maximum lateness. In both cases, maintenance must be performed within a fixed period T, and the time for the maintenance is a decision variable. In this paper, we study two scenarios concerning the planning horizon. First, we show that, when the planning horizon is long in relation to T, the problem with either objective function is NP-complete, and we present pseudopolynomial time dynamic programming algorithms for both objective functions. In the second scenario, the planning horizon is short in relation to T. However, part of the period T may have elapsed before we schedule any jobs in this planning horizon, and the remaining time before the maintenance is shorter than the current planning horizon. Hence we must schedule one maintenance in this planning horizon. We show that the problem of minimizing the total weighted completion times in this scenario is NP-complete, while the shortest processing time (SPT) rule and the earliest due date (EDD) rule are optimal for the total completion time problem and the maximum lateness problem respectively. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 845–863, 1999     

Note: Minimizing the variability of the waiting times in a globally gated elevator polling system

A polling system comprising n queues and a single server is considered. Service is performed according to an elevator scheme under the globally gated regime. The problem of arranging the channels to minimize a measure of the variability of the waiting times is addressed. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 605–611, 1997     

Asia-Pacific Demand for Military Expenditure: Spatial Panel and SUR Estimates

This article investigates the demand for military expenditure for a sample of key Asia-Pacific countries. Spatial panel demand estimates are presented for three joined spatial units using a fixed-coefficient spatial lag model based on a two-step efficient GMM estimator. Spatial autoregression estimates are next presented for 1991–2015, founded on alternative kinds of country connectivities, such as contiguity, inverse distance, discrete distance, and power-projection considerations. Finally, 11 select countries’ demands for defense equations are estimated using seemingly unrelated regressions. From alternative perspectives, these estimated models indicate how Asia-Pacific countries respond to the defense spending of other countries. In the spatial runs, free riding is prevalent despite the growing military might of China, which apparently is not generally viewed as a threat. For the sample period, the projection of Chinese or American power is a relevant spatial factor. The main threat is reflected in non-U.S. allies’ reaction to U.S. allies’ defense spending during 1991–2015 and to Chinese defense spending after 2002.     

Decomposing inventory routing problems with approximate value functions

We present a time decomposition for inventory routing problems. The methodology is based on valuing inventory with a concave piecewise linear function and then combining solutions to single‐period subproblems using dynamic programming techniques. Computational experiments show that the resulting value function accurately captures the inventory's value, and solving the multiperiod problem as a sequence of single‐period subproblems drastically decreases computational time without sacrificing solution quality. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010