Genetic algorithms for inventory constrained scheduling on a single machine

This paper focuses on Single machine scheduling subject to inventory constraints. Jobs add and remove items to and from, respectively, the inventory. Jobs that remove items cannot be processed if the required number of items is not available. We consider scheduling problems on a Single machine with regular objective functions Lmax ∑wjCj, ∑wjUj and ∑wjTj, and propose a genetic algorithm framework to tackle them. The focus is on discussion of different representations with respect to redundancy and corresponding decoding schemes. Moreover, we evaluate the different techniques by means of a computational study.