A two-stage stochastic programming model for lot-sizing with onsite generation of renewable energy
Abstract
One way to achieve energy efficiency in manufacturing consists of equipping plants with
on-site renewable energy generation systems to partially power industrial processes. However,
renewable energy sources are highly intermittent and their availability is difficult to be predicted
accurately. We thus investigate an integrated industrial production planning and energy supply
problem under uncertain renewable energy availability. We propose a two-stage stochastic
programming model for this problem. The first decision stage consists of building a production
plan for a proportional lot-sizing and scheduling problem in a single-machine multi-item setting.
The second decision stage considers a discrete set of scenarios representing potential realizations
of the stochastic generation of renewable energy over the planning horizon and aims at building
an energy supply plan for each scenario. Computational experiments will be presented to show
the practical efficiency of the proposed approach.
Domains
Operations Research [math.OC]
Origin : Files produced by the author(s)