To decompose an unbalanced multi-stage logistic system to multipleindependent single-stage logistic systems, a new notion of parameterized interface distribution ispresented. For encoding the logistic pattern on each ...To decompose an unbalanced multi-stage logistic system to multipleindependent single-stage logistic systems, a new notion of parameterized interface distribution ispresented. For encoding the logistic pattern on each stage, the Pruefer number is used. With theimproved decoding procedure, any Pruefer number produced stochastically can be decoded to a feasiblelogistic pattern, which can match with the capacities of the nodes of the logistic system. Withthese two innovations, a new modeling method based on parameterized interface distribution and thePriifer number coding is put forward. The corresponding genetic algorithm, named as PIP-GA, can findbetter solutions and require less computational time than st-GA. Although requiring a little moreconsumption of memory, PIP-GA is still an efficient and robust method in the modeling andoptimization of unbalanced multi-stage logistic systems.展开更多
This paper deals with reductions of ideals in various settings of pullback constructions.Precisely,we investigate reductions of several types of ideals in both generic and classical pullbacks.We also characterize pull...This paper deals with reductions of ideals in various settings of pullback constructions.Precisely,we investigate reductions of several types of ideals in both generic and classical pullbacks.We also characterize pullbacks where reductions of a class of ideals extend to reductions of their respective extended ideals.All results are illustrated with original examples.展开更多
文摘To decompose an unbalanced multi-stage logistic system to multipleindependent single-stage logistic systems, a new notion of parameterized interface distribution ispresented. For encoding the logistic pattern on each stage, the Pruefer number is used. With theimproved decoding procedure, any Pruefer number produced stochastically can be decoded to a feasiblelogistic pattern, which can match with the capacities of the nodes of the logistic system. Withthese two innovations, a new modeling method based on parameterized interface distribution and thePriifer number coding is put forward. The corresponding genetic algorithm, named as PIP-GA, can findbetter solutions and require less computational time than st-GA. Although requiring a little moreconsumption of memory, PIP-GA is still an efficient and robust method in the modeling andoptimization of unbalanced multi-stage logistic systems.
文摘This paper deals with reductions of ideals in various settings of pullback constructions.Precisely,we investigate reductions of several types of ideals in both generic and classical pullbacks.We also characterize pullbacks where reductions of a class of ideals extend to reductions of their respective extended ideals.All results are illustrated with original examples.
