Evolutionary tabu search for flexible due-date satisfaction in fuzzy job shop scheduling

We consider the job shop scheduling problem with fuzzy sets modelling uncertain durations and flexible due dates. With the goal of maximising due-date satisfaction under uncertainty, we first give a new measure of overall due-date satisfaction in this setting. Then, we define a neighbourhood structure for local search, analyse its theoretical properties and provide a neighbour-estimation procedure. Additionally, a tabu search procedure using the neighbourhood is combined with a genetic algorithm, so the resulting memetic algorithm, guided by the defined due-date satisfaction measure, is run on a set of benchmarks. The obtained results illustrate the potential of our proposal. (C) 2020 Elsevier Ltd. All rights reserved.