| dc.description.abstract | Dynamic job shop scheduling problem (DJSSP) plays a role in modern manufacturing
due to the emergence of dynamic-event in real time: new job arrivals, processing time
changes , machine breakdowns, and job cancellations. Objective of study was to
minimize makespan in a production environment. Artificial Bee Colony (ABC)
algorithm integrated with Tabu Search (TS) and rescheduling strategy was proposed to
efficiently deal with these dynamic events in production environments. The research
method involved developing mathematical model for small-size instance and using the
HABC algorithm for large-size instance. The HABC algorithm integrated the cluster
group roulette method and the Crossover Operator to improve searching and mining
capabilities. Experimental design indicated that the proposed HABC is better than
traditional methods in both solution quality and computational efficiency, demonstrating
its accuracy, flexibility, and ability to quickly adapt to changing events. The conclusions
highlighted the algorithm's ability to significantly improve scheduling performance in
dynamic manufacturing environments, social, and economic impacts, along with
recommendations for future research to develop better optimization techniques. | en_US |
