Determination of the best main serial chain in nonserial dynamic programming networks

Nonserial network structures abound in production lines, chemical processing systems, communication networks and many other multi-stage decision processes. Algorithms based on dynamic programming have been developed to solve these systems. In solving these nonserial systems it turns out that the storage demand largely depends on the choice of the main serial chain in the network, i.e., the chain of stages to which the loops are connected. The purpose of this paper is to determine the best main serial chain that minimizes the storage demand in the looped networks. Based on complexity analysis, the characteristics of the best main serial chain in various nonserial loop structures are examined. A graph theoretic approach is employed for the problem of finding the best main chain in those systems.