In grid-connected photovoltaic (PV) systems, an effective control strategy is needed for an efficiently use of solar energy as well as for energy supplies optimization.
Three case studies are presented: identifying the optimal strategy to deal with supply disruptions, optimization of design decisions regarding additional capacity investments, and optimization of policies' parameters.
Location analysis and network design are two major research areas in supply chain optimization; location problems deal with the decisions of where to optimally locate facilities, whereas network design involves activating optimal links (Contreras and Fernández 2012).
This chapter discusses the results of a research conducted on a solar photovoltaic (PV) powered remote located community with the goals of: designing a reliable autonomous PV power system to supply electricity, optimization of size of components in the system, and improvement of capital cost due to size optimization.
"Substitution scenarios can be run through the application to search for alternatives that may lower both GHGs and cost, and result in a supply chain optimization opportunity".
Jamshidi et al. (2015) presented flexible supply chain optimization with controllable lead time and shipping option.
The aim of most supply chain optimization problems is to minimize the total cost of the supply chain.
Zamboni et al. (2009) proposed the bioethanol supply chain optimization in which they presented a model for the strategic design of biomass-based fuel supply networks.
In this paper, firstly the presented works for biofuel supply chains optimization are systematically reviewed and categorized.
The use of advanced algorithmic approaches such as machine learning may have application to bioprocess and supply chain optimization.
