| dc.description.abstract | This paper aims to present a research-based model of scheduling harvesting problems.
It states that this sector has made significant improvements in recent years in figuring
out how to optimize the cost in the supply chain of paddy rice. In this paper, based on
the previous methods, I extend an existing approach and add more external factors to
deal with harvesting scheduling problems. On the other hand, there are two
mathematical models with specific parameters applied to solve sperate problems:
minimize the travelling distance for small fields and operation cost for large fields, by
more complexible data which approach clearly with reality. The framework paper
described here is both simple and universal aim for comparison outputs with historical
data. The paper finds that significant results can be conducted for optimizing the outputs
when using these models and harvesting plan could be built for company reference.
Moreover, to enhance these outputs, I also apply Adaptive Large Neighborhood Search
(ALNS). The key limitation in this research lies in the difficulty in linking two sperate
models. For further research, I would like to expand to consider more external factors
and create a consistent model to analysis | en_US |
