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

Year: 2025

Type: article

Abstract: 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.

Source: Environment-Behaviour Proceedings Journal

DOI: 10.21834/e-bpj.v10isi31.6939

Authors: Mansir Abubakar, Alwatben Batoul Rashed, Sanusi Abu Darma, Mardiyya Lawal Bagiwa

Institutions: Universiti Teknologi MARA System, Universiti Teknologi MARA, Qassim University, Al-Qalam University Katsina

Language: English

Topic: Scheduling and Optimization Algorithms

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: diamond

Funder: Universiti Teknologi MARA

OpenAlex ID: W4412188031

FWCI:

Cites: 11

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Related to: 10