On scheduling with ready-times,due-dates and vacations

A single machine sequencing problem is considered in which there are ready-time and due-date constraints on jobs and vacation constraints on the machine. Each vacation has fixed starting and finish time and no preemption is allowed for the jobs. The objective is to minimize maximum lateness. An intriguing feature of this formulation is that it allows sequencing in disconnected time windows. A relaxation of the problem is obtained by modeling the vacations as a set of jobs with flexible ready-times and artificial due-dates and a branch and bound algorithm is developed for the problem. In the algorithm, the search is not only guided by the bounds but also by a careful manipulation of the artificial due-dates. Consequently; while searching in the relaxed solution space, solutions of the original problem are implicitly enumerated. Computational results indicate that the algorithm can satisfactorily solve problems with multiple vacations.     

The survival probability function of a target moving along a straight line in a random field of obscuring elements

A target is moving along a straight-line path. Random portions of the path might be invisible to the hunter (in shadow). Shooting trials are conducted only along the visible segments of the path. An algorithm for the numerical determination of the survival probability of the target is developed. This algorithm is based on the distribution of shadow length, which is also developed. © 1994 John Wiley & Sons, Inc.     

A one-dimensional infiltration game

Minimax strategies are obtained for an infiltration game in which one player must move through a one-dimensional interval defended by the other player.     

A bayes approach to quality control of an M/G/1 queue

This article provides a Bayes approach for the quality control of a production process which is defined by an M/G/1 queue. An inspection procedure which is jointly optimal from the queue's operational characteristics and quality-control perspectives is found using a queue-inspection renewal cycle analysis (with overall expected profit per unit time as the optimization objective). Numerical results are obtained, highlighting the relationships between quality control and (queue-like) production management.     

A vertex-closing approach to the p-center problem

This article uses a vertex-closing approach to investigate the p-center problem. The optimal set of vertices to close are found in imbedded subgraphs of the original graph. Properties of these subgraphs are presented and then used to characterize the optimal solution, to establish a priori upper and lower bounds, to establish refined lower bounds, and to verify the optimality of solutions. These subgraphs form the foundation of two polynomial algorithms of complexity O(|E| log |E|) and O(|E|²). The algorithms are proven to converge to an optimum for special cases, and computational evidence is provided which suggests that they produce very good solutions more generally. Both algorithms perform very well on problems where p is large relative to the number of vertices n, specifically, when p/n ≥ 0.30. One of the algorithms is especially efficient for solving a sequence of problems on the same graph.     

Stochastic linear fractional programming with the ratio of independent Cauchy variates

In this article is studied a stochastic linear fractional programming problem, in which the parameters of both the numerator and the denominator are assumed to be mutually independent Cauchy variates. The deterministic equivalent of the problem is obtained and is shown to be a linear fractional program. A numerical example is also added for illustration.     

Robust preallocated preferential defense

The problem is to protect a set of T identical targets that may come under attack by A identical weapons. The targets are to be defended by D identical interceptors, which must be preallocated to defend selected targets. The attacker is aware of the number of interceptors, but is ignorant of their allocation. The size of the attack is chosen by the attacker from within a specified range. The robust strategies developed in this article do not require the defender to assume an attack size. Rather, the defender chooses a strategy which is good over a wide range of attack sizes, though not necessarily best for any particular attack size. The attacker, knowing that the defender is adopting a robust strategy, chooses the optimal attack strategy for the number of weapons he chooses to expend. The expected number of survivors is a function of the robust defense strategy and optimal attack strategy against this robust defense.     

Democracy for the rescue—of dictators? The role of regime type in civil war interventions

Intrastate conflicts, long eclipsing interstate conflicts, are often internationalized. This paper examines internationalized intrastate conflicts through the types of both the intervening and the embattled regimes. Do democracies, more or less than autocracies, support autocratic governments in their fights against rebels? This paper tests three hypotheses: (1) democracies support autocrats fighting rebels less than autocracies do. (2) Democracies support democratic governments fighting against rebels more than autocracies do. (3) The more democratic two states are, the higher the probability one would support the other’s fight against rebels. Covering all documented external support in intrastate wars (1975–2000), our findings support hypothesis one and two only partly and confirm hypothesis three. However, comparing the two major accounts of the Democratic Peace theory (DPT)—the normative and the structural—our findings corroborate only the former robustly. The paper thus helps enriching the insights of the DPT beyond interstate conflicts.     

Optimal resource allocation and redistribution strategy in military conflicts with Lanchester square law attrition

We address the problem of optimal decision‐making in conflicts based on Lanchester square law attrition model where a defending force needs to be partitioned optimally, and allocated to two different attacking forces of differing strengths and capabilities. We consider a resource allocation scheme called the Time Zero Allocation with Redistribution (TZAR) strategy, where allocation is followed by redistribution of defending forces, on the occurrence of certain decisive events. Unlike previous work on Lanchester attrition model based tactical decision‐making, which propose time sequential tactics through an optimal control approach, the present article focuses on obtaining simpler resource allocation tactics based on a static optimization framework, and demonstrates that the results obtained are similar to those obtained by the more complex dynamic optimal control solution. Complete solution for this strategy is obtained for optimal partitioning of resources of the defending forces. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Changing the paradigm: Simulation,now a method of first resort

Decades ago, simulation was famously characterized as a “method of last resort,” to which analysts should turn only “when all else fails.” In those intervening decades, the technologies supporting simulation—computing hardware, simulation‐modeling paradigms, simulation software, design‐and‐analysis methods—have all advanced dramatically. We offer an updated view that simulation is now a very appealing option for modeling and analysis. When applied properly, simulation can provide fully as much insight, with as much precision as desired, as can exact analytical methods that are based on more restrictive assumptions. The fundamental advantage of simulation is that it can tolerate far less restrictive modeling assumptions, leading to an underlying model that is more reflective of reality and thus more valid, leading to better decisions. Published 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 293–303, 2015