A mixed integer optimization approach for simultaneous data reconciliation and identification of measurement bias

Abstract

Abstract The problem of data reconciliation and the detection and identification of gross errors, such as measurement bias, are closely related. This close relationship prompted the development of a technique that combines these ideas within a mixed integer optimization framework. This paper describes such an approach and demonstrates its performance with a challenging test problem.