A Quick Knapsack Heuristic Solution for Pharmaceutical RD Pipeline Management Problems

摘要

The paper presents a novel knapsack decomposition algorithm for solving multistage stochastic programs (MSSPs) with endogenous uncertainty, specifically focusing on pharmaceutical R&D pipeline management problem. The algorithm decomposes the MSSP into a series of knapsack problems, which are created and solved at key decision points on a rolling horizon fashion. Based on the results of the five case studies, the algorithm generates implementable solutions with several orders of magnitude decrease in the CPU times required to solve the rigorous MSSP.