Investigating Artificial Immune Systems For Job Shop Rescheduling In Changing Environments

TL;DR

This paper explores how artificial immune systems can be used for resilient job shop rescheduling in dynamic environments, aiming to improve schedule quality while maintaining robustness.

Contribution

It proposes a method to enhance schedule quality in artificial immune systems without compromising their robustness in changing environments.

Findings

Artificial immune systems outperform genetic algorithms in robustness.

Increasing antigens improves schedule quality but affects fitness.

Rescheduling with the same method can maintain robustness while improving results.

Abstract

Artificial immune system can be used to generate schedules in changing environments and it has been proven to be more robust than schedules developed using a genetic algorithm. Good schedules can be produced especially when the number of the antigens is increased. However, an increase in the range of the antigens had somehow affected the fitness of the immune system. In this research, we are trying to improve the result of the system by rescheduling the same problem using the same method while at the same time maintaining the robustness of the schedules.