An Effective Job Scheduling for Maximum Resource Utilisation with Particle Swarm Optimisation

This paper focuses on optimizing job schedules using Particle Swarm Optimization (PSO). The goal is to find a schedule that minimizes the time needed to complete all tasks. The algorithm is chosen as it can achieve fast convergence due to its swarm intelligence behavior and its capability to search in a global space. The results show that PSO can minimize the time of the job schedule effectively. This is very helpful for businesses in managing their resources efficiently, thus, reducing the cost. It benefits industries that involve complex scheduling such as manufacturing and logistics. The paper highlights the capabilities of PSO in optimizing job schedules and could be applied to solve various problems across different domains.