AUGMECON-Py: A Python framework for multi-objective linear optimisation under uncertainty

Abstract This paper presents AUGMECON-Py, a Python framework for solving large and complex multi-objective linear programming problems under uncertainty, optimally robustly capturing all solutions. On the core of AUGMECON-Py software lies integration well-established optimisation algorithm (AUGMECON) with Monte Carlo analysis that helps maximise robustness against stochastic thereby avoiding complexity numerous cascading methods code scripts. Using an object-oriented language, overcomes limitations its predecessors regarding memory requirements, further extends solution to ensure no efficient is left outside grid. The easily accessible, offering effortless data pre- post-processing, management, visualisation results.