The random nature of soil loss under alternative land-use practices should be an important consideration of soil conservation planning and analysis under risk. Chance constrained programming models ...can provide information on the trade-offs among pre-determined tolerance levels of soil loss, probability levels of satisfying the tolerance levels, and economic profits or losses resulting from soil conservation to soil conservation policy makers. When using chance constrained programming models, the distribution of factors being constrained must be evaluated. If random variables follow a log-normal distribution, the normality assumption, which is generally used in the chance constrained programming models, can bias the results.
The random nature of soil loss under alternative land-use practices should be an important consideration of soil conservation planning and analysis under risk. Chance constrained programming models ...can provide information on the trade-offs among pre-determined tolerance levels of soil loss, probability levels of satisfying the tolerance levels, and economic profits or losses resulting from soil conservation to soil conservation policy makers. When using chance constrained programming models, the distribution of factors being constrained must be evaluated. If random variables follow a log-normal distribution, the normality assumption, which is generally used in the chance constrained programming models, can bias the results.
The random nature of soil loss under alternative land-use practices should be an important consideration of soil conservation planning and analysis under risk. Chance constrained programming models ...can provide information on the trade-offs among pre-determined tolerance levels of soil loss, probability levels of satisfying the tolerance levels, and economic profits or losses resulting from soil conservation to soil conservation policy makers. When using chance constrained programming models, the distribution of factors being constrained must be evaluated. If random variables follow a log-normal distribution, the normality assumption, which is generally used in the chance constrained programming models, can bias the results.
Production control implications for CIMS Sarin, S.C.; Das, S.K.
Proceedings 1988 International Conference on Computer Integrated Manufacturing,
1988
Conference Proceeding
The implications and importance of production control for CIM (computer-integrated manufacturing) are discussed. To better understand what these implications are, a list of twenty desirable ...attributes of computer integrated production planning and control (CIPP&C) systems are presented. The list is neither exhaustive nor mandatory. It is in a sense a wish list and it is unlikely that any one system will incorporate all the features. But, it is important that the development of the features be approached in an attempt to integrate them in CIPP&C systems. A brief review of current methodologies incorporating some of these attributes is reported.< >
