DYNAMIC-PROGRAMMING ALGORITHM FOR DECISION CPM NETWORKS

A dynamic programming algorithm is proposed for decision CPM (DCPM) networks. DCPM is a natural, powerful, and general way of handling the discrete-time/cost-tradeoff problem. Solution approaches developed to date have not been efficient enough to handle realistically sized problems. The main approaches have been general integer programming algorithms and the specialized branch-and-bound methods for DCPM of Crowston and Wagner. Both of these approaches have many inherent shortcomings: solution times grow exponentially with the number of decision nodes, storage requirements quickly become excessive, pre-processing or decomposition of the problem must be undertaken before the algorithms themselves can be called upon to solve the problem, and large variations in solution times have been based on differences in the structure of the problem. The algorithm presented overcomes all of these shortcomings.