Optimized Lease Planning for Real Estate Portfolios

Abstract

Real Estate has long been the second highest annual operating expense for companies after labor cost. However, real estate decisions are also intimately connected with productivity and company success. Real Estate portfolios therefore need to be both cost-effective and aim for an efficient utilization of space through optimized decisions on which leases should be adopted, dropped or extended. These require an intelligent decision framework that considers economic and performance metrics. We introduce an Integer Linear Programming formulation for Portfolio optimisation. The modelling framework identifies and evaluates several metrics that make certain leases preferrable to others. We conduct numerical simulations on Lease Datasets in a Real Estate Portfolio Management of 5000 buildings.