Robust multi-objective job-shop scheduling for make-to-order manufacturing

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Effective order sequencing and task scheduling has become a necessity for survival in today's competitivemarkets. Scheduling in a manufacturing environment concerns with translating released orders into jobs withassociated due dates and allocating them to designated workstations. Job-shop scheduling is a multi-objectivecombinatorial optimization problem. Nonetheless, the majority of scheduling algorithms are usually efficientunder a given objective function rather than a combination of them. Furthermore, unforeseen events on theshop floor, such as machine break-downs along with rush/canceled orders may have a significant impact on theschedule. In order to reduce the need for major changes in the initial schedule, robustness criteria should beincorporated into scheduling models.In this project, the applicant will team up with Festo Didactic Ltd. in order to overcome the challenges thecompany has been recently confronted in scheduling the continuously increasing sales. The main goal is todevelop a library of algorithmic procedures for robust multi-objective job-shop scheduling. The first steptowards achieving this goal would be the characterization of the specific scheduling problem via investigationof manufacturing processes corresponding to different product families. Identification of variousdecision-making criteria with corresponding priorities in addition to the most pertinent sources of disruptionswill be also an essential step in the project. The new scheduling engine that is expected to be integrated intotheir current production planning software will incorporate a set of basic and composite dispatching rules alongwith local search and metaheuristic algorithms to generate alternative schedules. Developing a discrete-eventsimulation model for the purpose of assessing the performance of generated schedules would be also within therealm of this research project.The results of this project will provide essential benefits to the company in terms of manufacturing lead-timeand work-in-process inventory reduction. Furthermore, the developed scheduling engine can be incorporated