The goal of this study is to make the government/users decide rationally with regards to the problems of the weapon systems management. Therefore it is necessary to develop how much precisely and through what methods the system should be cost. That costing policies should be determined under the considerations of the estimating expense and the expected benefit due to the applications of cost informations. After that, it must also be decided where the cost informations are used. We can suggest the cost results be used to find the most reasonable system among alternatives, the best producer, the most benevolent policy for user, and so on.

In cost-only incentive contract the emphasis is the attainment of efficient and effective cost control. In contrast multiple incentives contract correlates contractor's profit motives with the generalized government objective function, the decision variables of which are performance or quality (technical progress), time or schedule (timely development and delivery) and the cost (efficient and effective cost control) Under multiple incentive structure, it is essential to formulate the trade-off curves between cost and performance, which are called iso-fee curves. Trade-off curves depict the combination of cost and performance achievement for which the contractor will be rewarded with the same fee. The basic function of trade-off curves is to show he the contractor will be motivated by incentive arragement to trade off or sacrifice the achievement in one incentive element for the acnievment in another.

An effectively designed budget system in the poor resources environment necessarily has three design criteria : (i) to be both planning-oriented and control-oriented, (ii) to be both rationalistic and realistic, (iii) to be sensitive to the variations of resources environment. PPB system is an extreme (planning-oriented and rationalistic) and conventional OEB/OUB system is the other extreme (control-oriented and incrementalistic). Generally, the merits of rationalism are limited because of the infeasibility of applications. Hence, mixtures of the two extremes such as MBO, ZBB, and RZBB have been examined and applied during the last decade. The classical mathematical models of capital budgeting are the starting points of the development of the Budget-Mix Model introduced in this paper. They are modified by the followings: (i) technological-resource constraints, (ii) bounded-variable constraint, (iii) the exchange rules. Special emphasis is laid on the above (iii), because we need more efficient interresource exchanges in the budget-mix process. The Budget-Mix Model is not based on optimization, but a heuristic approach which assures a satisficing solution. And the application fields of this model range between the incremental Nonzero-Base Budgeting and the rational Zero-Base Budgeting. In this thesis, the author suggests 'the budget- mix concept' and a budget-mix model. Budget-mix is a decision process of making program-mix and resource-mix together. For keeping this concept in the existing organization realistic, we need the development of quantitative models describing budget-mix situations.

Stochastic duels have been studied by Ancker, William, Bhashyam, Gafarian, Jaiswal, Singh, and others, Stochastic duels are classified in terms of factors such as kill probability, ammunition, time duration, surprise, mobility, time of flight, etc. The purpose of this paper is to summarize and analyze the models of stochastic duels that have been studied so far, and to study the effect of the factors to the win probability.

An efficient algorithm which can be employed in obtaining the minimal cut sets of a fault tree containing repeated events is introduced. A sample fault tree illustrates this algorithm. Efficiency of an algorithm is defined as the ratio of the number of minimal cut sets to the number of cut sets determined by the algorithm. An efficiency of the proposed algorithm is compared with those of two existing algorithms : Fussell and Vesely's algorithm and Bengiamin et al. 's algorithm. The proposed algorithm is shown to be more efficient than the existing two algorithms.