Analysis of artillery shoot‐and‐scoot tactics

Firing multiple artillery rounds from the same location has two main benefits: a high rate of fire at the enemy and improved accuracy as the shooter's aim adjusts to previous rounds. However, firing repeatedly from the same location carries significant risk that the enemy will detect the artillery's location. Therefore, the shooter may periodically move locations to avoid counter‐battery fire. This maneuver is known as the shoot‐and‐scoot tactic. This article analyzes the shoot‐and‐scoot tactic for a time‐critical mission using Markov models. We compute optimal move policies and develop heuristics for more complex and realistic settings. Spending a reasonable amount of time firing multiple shots from the same location is often preferable to moving immediately after firing an initial salvo. Moving frequently reduces risk to the artillery, but also limits the artillery's ability to inflict damage on the enemy.     

求取鱼雷转角射击转角的实用算法

较为详细地推导了鱼雷转角射击公式,根据分鱼雷转向的不同总结出两类求解公式（各种态好都能用两类公式之一来解算）．最后还讨论了所导出的非线性方程的数值解算方法,该算法具有工程应用价值。     

Landmarks in Defense Literature

Victory through Air Power, Air Power Key to Survival and America: Too Young to Die. By Alexander P. De Seversky     

Waiting time distributions for transient bulk queues with general vehicle dispatching strategies

A numerical approach is presented for determining the waiting time distribution in a transient bulk-arrival, bulk-service queue. Vehicle departures from the queue are governed by a general dispatch strategy that includes holding with a variable release function and vehicle cancellations. The waiting time distribution of a customer (in a group) arriving at a given point in time is calculated by simulating the process in discrete time and determining at each step the probability the customer has left the system. The dispatch strategies require knowing the total length of the queue as well as the position a customer holds in the queue. An exact approach is compared to an accurate approximation which is 50 to 100 times faster. Comparisons are made with other approaches in the context of steady-state systems.     

Two heuristics for the economic lot scheduling problem: An experimental study

In this article we present and test two heuristics for the economic lot scheduling problem. The first heuristic was developed by one of us (P.C. Geng) during Ph.D. research, while the other is a convergent implementation of an algorithm due to Doll and Whybark. We study the performance of these heuristics on a large set of test problems constructed using a new form of problem generation that yields random problems within an experimental design.