Efficient scheduling of a real case study of the pharmaceutical industry using a mathematical-algorithmic decomposition methodology

Abstract

This work presents a mathematical-algorithmic methodology to handle scheduling decisions on multiproduct multistage batch facilities, developed with the aim to solve problems of industrial size. The proposal is based on the iterative construction of a solution by solving a sequence of subproblems associated to each stage, identifying and fixing the critical decisions at each step, and keeping rigorous information on the bounds. The methodology is applied to a real case study obtaining good quality solutions in competitive computing times.