This paper considers manufacturing planning and scheduling of manufacturing orders whose value decreases over time. The value decrease is modelled with a so-called value curve. Two genetic-algorithm-based methods for multi-objective optimisation have been proposed, implemented and deployed to a cloud. The first proposed method allocates and schedules manufacturing of all the ordered elements optimising both the makespan and the total value, whereas the second method selects only the profitable orders for manufacturing. The proposed evolutionary optimisation has been performed for a set of real-world-inspired manufacturing orders. Both the methods yield a similar total value, but the latter method leads to a shorter makespan.
@article{arxiv.1912.01562,
title = {Value-driven Manufacturing Planning using Cloud-based Evolutionary Optimisation},
author = {Shuai Zhao and Piotr Dziurzanski and Leandro Soares Indrusiak},
journal= {arXiv preprint arXiv:1912.01562},
year = {2020}
}
Comments
This paper is an extended version of a paper published at International Conference on Manufacturing Science and Technology (ICMST) in 2019. In this version, we have updated the evaluation section to provide experimental setup and results that are more realistic and suitable to the proposed approach