Resource Optimization in Job-shop Scheduling using Ant-Colony-Optimization Metaheuristic: ACO Algorithm to Resolve Scheduling Problem - Khan, Shahid A.; Alam, Muhammad A.; Umer, Muhammad (Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences, 2021)
Present study elucidates the probity of ant colony optimization metaheuristic in minimizing the makespan by efficiently allocating jobs to workstations in general aviation maintenance. The metaheuristic technique is applied to real workplace problems in general aviation sector of Pakistan to resolve scheduling quandaries of XT-10 helicopters inspection in Burq Air Services (Pseudo names of organization and helicopter to keep anonymity). Secondary data for processing times of jobs at workstations was obtained from job cards and process sheets. Matlab codes were developed for reaching the optimal scheduling. Results indicated almost 25% improvement in efficiency, and proffered a customized yet efficient solution to scheduling problem in real aviation maintenance setup. The study posited that with the slight adjustment, the present model could be applied to other variants of job-shop, service industry, and similar areas of social sciences.