Optimization instances for deterministic and stochastic problems on energy efficient investments planning at the building level

• Main Authors: Emilio L. Cano, Javier M. Moguerza, Antonio Alonso-Ayuso
• Format: Article
• Language: English
• Published: Elsevier 2015-12-01
• Series: Data in Brief
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352340915002693

Optimization instances relate to the input and output data stemming from optimization problems in general. Typically, an optimization problem consists of an objective function to be optimized (either minimized or maximized) and a set of constraints. Thus, objective and constraints are jointly a set of equations in the optimization model. Such equations are a combination of decision variables and known parameters, which are usually related to a set domain. When this combination is a linear combination, we are facing a classical Linear Programming (LP) problem. An optimization instance is related to an optimization model. We refer to that model as the Symbolic Model Specification (SMS) containing all the sets, variables, and parameters symbols and relations. Thus, a whole instance is composed by the SMS, the elements in each set, the data values for all the parameters, and, eventually, the optimal decisions resulting from the optimization solution. This data article contains several optimization instances from a real-world optimization problem relating to investment planning on energy efficient technologies at the building level.