Optimization metaheuristics for minimizing variance in a real-world statistical application
Estevao de O. da Costa, Fábio Fabris, Alexandre Rodrigues Loureiros, Hannu Ahonen, Flávio Miguel Varejão · 2013
Non-technical energy losses mostly arise from illegal use of energy. Energy distribution companies need to estimate the sources of these losses in order to take actions for reducing them. In this work we formulate a stratified sampling procedure as a non-linear restricted optimization problem, in which the variance of overall energy loss due to the fraudulent activities is minimized. Solving this problem analytically is difficult and therefore we customize two metaheuristics, Genetic Algorithm and Simulated Annealing, for finding practical solutions for the problem. Numerical experiments and comparison to a proportional allocation scheme are presented.