Energy-aware foundry production scheduling

Foundries are a very energy-demanding industry due to the intensive use of furnaces which purpose is to melt metallic resources. Nowadays, the scheduling of the orders and the optimisation of the foundry process itself is carried out based on expert knowledge acquired over years of experience, loosely taking into account energy costs and hourly electricity prices. This paper contributes to the state of the art by applying, for the first time, a set of genetic, simulated annealing and backtracking algorithms to the foundry scheduling problem, empirically demonstrating with real data that such approach is sound, feasible and provides better results than classical methods.