文章介绍了 NASA 在1993年提出的空间环境及效应(下称 SEE)计划,其目的是明确空间环境的定义,为设计、研制能适应严酷空间环境效应的航天器系统并使其正常运行提供技术支持。该计划包括认识空间环境、飞行试验和地面试验技术的优化、更...文章介绍了 NASA 在1993年提出的空间环境及效应(下称 SEE)计划,其目的是明确空间环境的定义,为设计、研制能适应严酷空间环境效应的航天器系统并使其正常运行提供技术支持。该计划包括认识空间环境、飞行试验和地面试验技术的优化、更新空间环境及其效应的预测模型、保存信息并将之纳入航天器的设计流程等方面。文章描述了 SEE 计划目前已取得的成就和未来的打算。展开更多
A technique is developed for finding a closed form expression for the cumulative distribution function of the maximum value of the objective function in a stochastic linear programming problem, where either the object...A technique is developed for finding a closed form expression for the cumulative distribution function of the maximum value of the objective function in a stochastic linear programming problem, where either the objective function coefficients or the right hand side coefficients are continuous random vectors with known probability distributions. This is the “wait and see” problem of stochastic linear programming. Explicit results for the distribution problem are extremely difficult to obtain;indeed, previous results are known only if the right hand side coefficients have an exponential distribution [1]. To date, no explicit results have been obtained for stochastic c, and no new results of any form have appeared since the 1970’s. In this paper, we obtain the first results for stochastic c, and new explicit results if b an c are stochastic vectors with an exponential, gamma, uniform, or triangle distribution. A transformation is utilized that greatly reduces computational time.展开更多
文摘文章介绍了 NASA 在1993年提出的空间环境及效应(下称 SEE)计划,其目的是明确空间环境的定义,为设计、研制能适应严酷空间环境效应的航天器系统并使其正常运行提供技术支持。该计划包括认识空间环境、飞行试验和地面试验技术的优化、更新空间环境及其效应的预测模型、保存信息并将之纳入航天器的设计流程等方面。文章描述了 SEE 计划目前已取得的成就和未来的打算。
文摘A technique is developed for finding a closed form expression for the cumulative distribution function of the maximum value of the objective function in a stochastic linear programming problem, where either the objective function coefficients or the right hand side coefficients are continuous random vectors with known probability distributions. This is the “wait and see” problem of stochastic linear programming. Explicit results for the distribution problem are extremely difficult to obtain;indeed, previous results are known only if the right hand side coefficients have an exponential distribution [1]. To date, no explicit results have been obtained for stochastic c, and no new results of any form have appeared since the 1970’s. In this paper, we obtain the first results for stochastic c, and new explicit results if b an c are stochastic vectors with an exponential, gamma, uniform, or triangle distribution. A transformation is utilized that greatly reduces computational time.
