Integrated capacity and production planning in the pharmaceutical supply chain: framework and models

Production planning is widely studied, and mathematical formulations have been proposed for various problems. The capacity level is usually fixed which requires a separate solution of the capacity planning problem. In this paper, a methodology is proposed for setting up and solving integrated capacity and production planning problems for a given manufacturing network. Mixed-integer linear programming problems are assembled from a constraint and objectives database based on a system characterization and their solution determines whether capacity levels should be changed. An indirect approach to solving the problem is suggested, in which the required capacities are determined with no knowledge of specific ways on how the capacity could be changed corresponding to an early stage of capacity planning. This contrasts with the traditional direct approach, in which a set of options are given and a subset of these chosen through optimization. The methodology is applied to three case studies from primary pharmaceutical manufacturing. A literature example is used to validate the method and two larger case studies show the method's ability to solve problems of industrial scale and relevance.