Statistical analysis of the output data from terminating simulations

In this paper we precisely define the two types of simulations (terminating and steady-state) with regard to analysis of simulation output and discuss some common measures of performance for each type. In addition, we conclude, on the basis of discussions with many simulation practitioners, that both types of simulations are important in practice. This is contrary to the impression one gets from reading the simulation literature, where the steady-state case is almost exclusively considered. Although analyses of terminating simulations are considerably easier than are those of steady-state simulations, they have not received a careful treatment in the literature. We discuss and give empirical results for fixed sample size, relative width, and absolute width procedures that can be used for constructing confidence intervals for measures of performance in the terminating case.     

On the equivalence between the Node-ARC and ARC-Chain formulations for the multi-commodity maximal flow problem

The purpose of this article is to formulate the multi-commodity maximal flow problem into a node-arc form and to show that when decomposition is applied to this form the resulting master and subproblems become precisely those described by Ford & Fulkerson [3] using the arc-chain formulation. A generalization to the problem is then considered which can potentially speed its convergence.     

Computational results for a stopping rule problem on averages

Suppose x₁, x₂, … are independently distributed random variables with Pr (x_i = 1) = Pr(x_i = ?1) = 1/2, and let s_n =

     

On a sequential rule for estimating the location parameter of an exponential distribution

Let us assume that observations are obtained at random and sequentially from a population with density function In this paper we consider a sequential rule for estimating μ when σ is unknown corresponding to the following class of cost functions In this paper we consider a sequential rule for estimating μ when σ is unknown corresponding to the following class of cost functions Where δ(X_I,…,X_N) is a suitable estimator of μ based on the random sample (X₁,…, X_N), N is a stopping variable, and A and p are given constants. To study the performance of the rule it is compared with corresponding “optimum fixed sample procedures” with known σ by comparing expected sample sizes and expected costs. It is shown that the rule is “asymptotically efficient” when absolute loss (p=-1) is used whereas the one based on squared error (p = 2) is not. A table is provided to show that in small samples similar conclusions are also true.     

Allocation of carrier-based attack aircraft using non-linear programming

The paper presents the formulation and several solutions of a model for allocating a fixed number of aircraft to carriers and to missions. The amount of damage that can be inflicted is maximized. A nonseparable concave nonlinear objective function expresses diminishing marginal damage. Linear constraints on aireraft, carrier space, and aircraft availability for missions are included. The model is solved using the sequential unconstrained minimization technique (SUMT). The model is presented in terms of a scenario. Several different exponential damage functions are treated, and S-shaped damage functions are discussed.     

A note on a comparison of confidence interval techniques in truncated life tests

Several approximate procedures are available in the literature for obtaining confidence intervals for the parameter A of an exponential distribution based on time truncated samples. This paper contains the results of an empirical study comparing three of these procedures.     

Differential game theoretic analysis of a problem of warfare

The present article considers a problem of missile warfare. It is formulated as a problem of economics and treated as a differential game. Some optimal strategies of targeting and firing of missiles are derived. Conditions under which such a war can be prevented are also developed.     

Vessel allocation by linear programming

This paper presents a linear programming model of a fleet of vessels which is required to transport quantities of cargo, such as coal, iron ore, limestone, and salt from certain producing ports to specific destination ports. This model has been implemented and is currently being used both for planning purposes and as an aid in scheduling the trips to be made by each vessel.