A nested layered network model for parallel solutions of discrete SPPs

A nested layered network mapping and algorithm is presented for parallel computational solutions of discrete stochastic programming problems with random coefficients. The algorithm is general purpose and efficiently implementable on multiprocessor systems with associative memory. Details of its implementation on a 64-CPU parallel computer and results are presented for a hard problem arising in antibody-inventory optimization in vitro. Performance is discussed along with scope vis-à-vis other general purpose efficient algorithms for discrete SPPs.