Evaluation of Simulation-Based Optimization in Grafting Labor Allocation
AffiliationUniv Arizona, Dept Syst & Ind Engn
Univ Arizona, Sch Plant Sci
Univ Arizona, Dept Agr & Resource Econ
MetadataShow full item record
CitationApplied Engineering in Agriculture. 34(3): 479-489. (doi: 10.13031/aea.12487) @2018
Rights© 2018 American Society of Agricultural and Biological Engineers
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractVegetable grafting is a labor-intensive operation with many management decisions. Labor management and resource planning are critical allocations in grafting nurseries, yet optimization is challenging due to the dynamic nature of workers' performance in vegetable seedling propagation. To this end, we developed a simulation-based optimization framework for labor management to optimize labor allocation. This approach was evaluated by comparing its result with those suggested by selected domain experts (a plant scientist and a nursery manager). Furthermore, the simulation models were validated with a dataset from a developing tomato grafting company. Simulation-based optimization is demonstrated as an effective approach to find the optimal/near optimal labor allocation for horticultural nurseries, where discrete event simulation is used to represent the dynamics of the grafting work environment and meta-heuristics are used to devise optimal/near optimal resource allocation strategies. Results reveal that a potential annual savings between $2,510 (0.6%) and $97,388 (20%) can be achieved for a grafting facility of 6 million plants per year.
VersionFinal published version
SponsorsU.S. Department of Agriculture (USDA) - National institute of food and agriculture [2016-51181-25404]