A genetic algorithm to achieve scheduling flexibility for a single machine problem
Résumé
We consider single machine scheduling problem with dynamic job arrival and total weighted tardiness and makespan as objective functions. The machine is subject to disruptions related to late raw material arrival and machine breakdowns. We propose a proactive-reactive approach to deal with possible perturbations. In the proactive phase, instead of providing only one schedule to the decision maker, we present a set of predictive schedules. This set is characterized by a partial order of jobs and a type of associated schedules, here semi-active schedules. This allows to dispose of some flexibility in job sequencing and flexibility in time that can be used on-line by the reactive algorithm to hedge against unforseen disruptions. In this paper, we focus on the proactive algorithm, which is based on a genetic algorithm and present some experimentations to validate that this algorithm is able, in several cases, to compute solutions (partial orders of jobs) that provide some flexibility while maintaining high shop performance.