‘Just another border incident’: The Rann of Kutch and the 1965 India–Pakistan War

ABSTRACT

The India–Pakistan War of September 1965 has attracted little attention in the larger body of work on South Asia. Further, almost nothing has been written on the earlier skirmish, in April 1965, between Indian and Pakistani security forces in the Rann-of-Kutch, an uninhabited salt marsh. This article argues that the limited conflict in the Rann, its immediate consequences, and its impact on Pakistani military and civilian leaders were central to Pakistan’s consideration of a military solution to the ongoing dispute in Kashmir, which then led to Indian retaliation and the outbreak of war.     

A survey of preventive maintenance models for stochastically deteriorating single-unit systems

A survey of the research done on preventive maintenance is presented. The scope of the present survey is on the research published after the 1976 paper by Pierskalla and Voelker [98]. This article includes optimization models for repair, replacement, and inspection of systems subject to stochastic deterioration. A classification scheme is used that categorizes recent research into inspection models, minimal repair models, shock models, or miscellaneous replacement models.     

Variance of the number of units produced on a transfer line with buffer inventories during a period of length T

The transfer-line models in the literature are planning models rather than operational models. That is, they are very useful for planning or designing the transfer line, but are less useful for controlling the daily operation of the line. The performance measure used in these models is the efficiency of the line A. The expected number of units produced during a period of length T cycles is AT. In this article a procedure is presented for calculating the variance of the number of units produced by the transfer line during a period of length T cycles. These two performance measures can be used to construct an interval estimate for, say, the number of units produced during a shift. This interval estimate is an operational guide for the production manager.     

Stochastic models for spread of motivating information

In this work we consider spread of information which motivates the hearer to perform some specified action. The time to completion of an action is assumed to be a random variable and the main focus is on the number of completed actions by time t, X(t). Some models, which reflect different degree of centralization in the spread process, are analyzed and the distribution of X(t), as well as that of some other stochastic processes of interest, are obtained. The relevance to propagation of epidemics is pointed out. All models are solved by employing two interrelated concepts, namely, the order statistics property of stochastic processes and the binomial closure property of collections of distributions. In this respect, the work also serves as an illustration of the application of these useful concepts.     

Preservation of unimodality under shock models

A number of results pertaining to preservation of aging properties (IFR, IFRA etc.) under various shock models are available in the literature. Our aim in this paper is to examine in the same spirit, the preservation of unimodality under various shock models. For example, it is proved that in a non-homogeneous Poisson shock model if {p_k}_K≥0, the sequence of probabilities with which the device fails on the kth shock, is unimodal then under some suitable conditions on the mean value function Λ (t), the corresponding survival function is also unimodal. The other shock models under which the preservation of unimodality is considered in this paper are pure birth shock model and a more general shock model in which shocks occur according to a general counting process. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 952–957, 1999     

Inspection policies for deteriorating equipment characterized by n quality levels

Inspection models deal with operating systems whose stochastic failure is detected by observations carried out intermittently. The current communication deals with systems in which N + 1 levels of quality can be diagnosed. Optimal policies leading to minimal loss are developed, while the system's distribution is represented by an (N + 1)-state semi-markov process. Based on previous studies of the authors, relative efficiencies of the proposed checking policies are ascertained, by comparison with the loss sustained if discrimination of quality by intermediate levels is disregarded and by viewing the system as one which is either good or failed. Various models are treated where checking, truncated checking, and monitoring policies optimize loss per cycle, per unit of time and per unit of good time. Numerical examples are given.     

Single-machine scheduling to minimize absolute deviation of completion times from a common due date

The article considers a single-machine n-job scheduling problem to minimize the sum of absolute lateness given a common due date. Two models are defined depending on whether the start time t₀ of schedules is arbitrary or fixed. Conditions are provided when those two models coincide. The developed branch-and-bound procedure is tested on nine known examples from the literature (6 ⩽ n ⩽ 14) and 90 medium-size random problems (15 ⩽ n ⩽ 25) with a fixed t₀.     

Single-machine scheduling of stochastic jobs subject to deterioration or delay

N jobs are available for processing by a single machine. Jobs make (stochastic) progress while being processed but deteriorate while awaiting processing. The pioneering work of Browne and Yechiali, who developed scheduling policies for such models, is extended (i) to incorporate a precedence relation on the job set, delimiting the class of admissible policies, and (ii) to preemptive scheduling models. For the latter, we demonstrate that under appropriate conditions there is an optimal policy which is nonpreemptive. This is also achieved for a class of preemptive models in which processing generates delays for waiting jobs. A single class of algorithms is shown to generate optimal policies for many of the problems considered. © 1992 John Wiley & Sons, Inc.     

Meanings of military ranks

This paper studies what kinds of meanings reserve officers ascribe to military ranks. The study builds on existing literature on reserve forces and hypothesizes that military ranks among reserve officers are subject to rendering the ranks with multiple meanings, and which are bound to create ambiguity of interpretation. To elaborate these theoretical insights a survey among Finnish reserve officers was conducted (N = 6193). The data was analyzed using factor analysis and correlation analysis. The results show that military ranks are ascribed, in addition to the functionalistic, hierarchical meaning, also with meanings of prestige, proficiency, and identity. The main theoretical contribution of the paper is in complementing the previous literature on ambiguity of military ranks by specifying four different meanings in the interpretation of the ranks.     

An alternative proof of the IFRA property of some shock models

Let , where A (t)/t is nondecreasing in t, {P(k)^1/k} is nonincreasing. It is known that H(t) = 1 — H (t) is an increasing failure rate on the average (IFRA) distribution. A proof based on the IFRA closure theorem is given. H(t) is the distribution of life for systems undergoing shocks occurring according to a Poisson process where P (k) is the probability that the system survives k shocks. The proof given herein shows there is an underlying connection between such models and monotone systems of independent components that explains the IFRA life distribution occurring in both models.     

Optimal (τ, T) opportunistic maintenance of a k‐out‐of‐n:G system with imperfect PM and partial failure

The opportunistic maintenance of a k‐out‐of‐n:G system with imperfect preventive maintenance (PM) is studied in this paper, where partial failure is allowed. In many applications, the optimal maintenance actions for one component often depend on the states of the other components and system reliability requirements. Two new (τ, T) opportunistic maintenance models with the consideration of reliability requirements are proposed. In these two models, only minimal repairs are performed on failed components before time τ and the corrective maintenance (CM) of all failed components are combined with PM of all functioning but deteriorated components after τ; if the system survives to time T without perfect maintenance, it will be subject to PM at time T. Considering maintenance time, asymptotic system cost rate and availability are derived. The results obtained generalize and unify some previous research in this area. Application to aircraft engine maintenance is presented. © 2000 John Wiley & Sons;, Inc. Naval Research Logistics 47: 223–239, 2000     

Monotone optimal preventive maintenance policies for stochastically failing equipment

This paper examines various models for maintenance of a machine operating subject to stochastic deterioration. Three alternative models are presented for the deterioration process. For each model, in addition to the replacement decision, the option exists of performing preventive maintenance. The effect of this maintenance is to “slow” the deterioration process. With an appropriate reward structure imposed on the processes, the models are formulated as continuous time Markov decision processes. the optimality criterion being the maximization of expected discounted reward earned over an infinite time horizon. For each model conditions are presented under which the optimal maintenance policy exhibits the following monotonic structure. First, there exists a control limit rule for replacement. That is, there exists a number i* such that if the state of machine deterioration exceeds i* the optimal policy replaces the machine by a new machine. Secondly, prior to replacement the optimal level of preventive maintenance is a nonincreasing function of the state of machine deterioration. The conditions which guarantee this result have a cost/benefit interpretation.     

Optimal maintenance models for systems subject to failure–A Review

This paper is a state-of-the-art review of the literature related to optimal maintenance models of systems subject to failure. The emphasis is on work appearing since the 1976 survey, “A Survey of Maintenance Models: The Control and Surveillance of Deteriorating Systems,” by W.P. Pierskalla and J.A. Voelker, published in this journal.     

Scheduling with earliest start and due date constraints

We consider the scheduling of n tasks on a single resource. Each task becomes available for processing at time a_i, must be completed by time b_i, and requires d_i time units for processing. The aim is to find a schedule that minimizes the elapsed time to complete all jobs. We present solution algorithms for this problem when job splitting is permitted and when job splitting is not permitted. Then we consider several scheduling situations which arise in practice where these models may apply.     

The effect of training data set size and the complexity of the separation function on neural network classification capability: The two-group case

Classification among groups is a crucial problem in managerial decision making. Classification techniques are used in: identifying stressed firms, classifying among consumer types, and rating of firms' bonds, etc. Neural networks are recognized as important and emerging methodologies in the area of classification. In this paper, we study the effect of training sample size and the neural network topology on the classification capability of neural networks. We also compare neural network capabilities with those of commonly used statistical methodologies. Experiments were designed and carried out on two-group classification problems to find answers to these questions. The prediction capability of the neural network models are better than traditional statistical models. The learning capability of the neural networks is improving compared to traditional models because the discriminate function is more complex. For real world classification problems, the usage of neural networks is highly recommended, for two reasons: learning capability and flexibility. Learning capability: Neural network classifies better in sterile experiments as performed in this research. Flexibility: Real life data are rarely not contaminated with noise, such as unknown distributions, and missing variables, etc. Neural networks differ from a statistical model that it is not dependent on any assumption concerning the data set distribution. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 699–717, 1997     

The dynamic transportation problem: A survey

The dynamic transportation problem is a transportation problem over time. That is, a problem of selecting at each instant of time t, the optimal flow of commodities from various sources to various sinks in a given network so as to minimize the total cost of transportation subject to some supply and demand constraints. While the earliest formulation of the problem dates back to 1958 as a problem of finding the maximal flow through a dynamic network in a given time, the problem has received wider attention only in the last ten years. During these years, the problem has been tackled by network techniques, linear programming, dynamic programming, combinational methods, nonlinear programming and finally, the optimal control theory. This paper is an up-to-date survey of the various analyses of the problem along with a critical discussion, comparison, and extensions of various formulations and techniques used. The survey concludes with a number of important suggestions for future work.     

Inventory models with a mixture of backorders and lost sales

This article presents several single-echelon, single-item, static demand inventory models for situations in which, during the stockout period, a fraction b of the demand is backordered and the remaining fraction 1 - b is lost forever. Both deterministic and stochastic demand are considered. although the case of stochastic demand is treated heuristically. In each situation, a mathematical model representing the average annual cost of operating the inventory system is developed. and an optimum operating policy derived. At the extremes b=1 and b=0 the models presented reduce to the usual backorders and lost sales cases, respectively.     

Economic screening procedures in logistic and normal models

Economic screening procedures based on a continuous screening variable X in place of a dichotomous performance variable T are presented. Optimal critical values on the screening variable minimizing the expected cost are obtained for two models; it is assumed that X given T is normally distributed in normal model and P[T = 1|X] is a logistic function of X in the logistic model, and that costs are incurred by screening inspection and misclassification errors. Cases where some parameters are unknown are also considered.