Energy considerations in a two machine flowshop scheduling problem with sequence dependent setups

Abstract

A two-machine flowshop permutation scheduling problem is addressed to minimize Cmax and energy consumption as conflicting criteria. We develop a mathematical formulation and propose a Multi-Objective Genetic Algorithm (MOGA) to find approximations of the Pareto front. Performance of the MOGA is compared with Cplex on various problems. The MOGA can support informed decision making via trade-off analysis between Cmax as a measure of service and energy consumption as a measure of sustainability.