Strategies for Source-to-Source Constant Propagation

Data-flow optimizations are usually implemented on low-level intermediate representations. This is not appropriate for source-to-source optimizations, which reconstruct a source level program after transformation. In this paper we show how constant propagation, a well known data-flow optimization problem, can be implemented on abstract syntax trees in Stratego, a rewriting system extended with programmable rewriting strategies for the control over the application of rules and dynamic rewrite rules for the propagation of information.     

DYNAMIC OPTIMAL CONTROL OF BATCH RICE DRYING PROCESS

The drying of paddy rice may result in quality degradation, expressed as a head kernel yield, leading to significant commercial depreciation of the product. A mathematical model of the drying and of the quality degradation process was combined with a dynamic optimization algorithm to determine the drying conditions (air temperature and relative humidity as functions of time) that ensured the highest possible final product quality for a specified drying time and a specified final moisture content. The robustness of the optimal drying strategy with respect to the initial state of the product, to the model parameters and to the initialization of the optimization algorithm was verified. The compromise between the highest achievable final quality and the allowed total drying time was studied. The combination of simulation and optimization yielded a new insight in the rice drying process and in the quality preservation strategies.