School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia.
PLoS One. 2023 Mar 15;18(3):e0282668. doi: 10.1371/journal.pone.0282668. eCollection 2023.
Production of cultivated resources require additional planning that takes growth time into account. We formulate a mathematical programming model to determine the optimal location and sizing of growth facilities, impacted by resource survival rate as a function of its growth time. Our method informs strategic decisions regarding the number, location, and sizing of facilities, as well as operational decisions of optimal growth time for a cultivated resource in a facility to minimize total costs. We solve this facility location and sizing problem in the context of coral aquaculture for large-scale reef restoration using a two-stage algorithm and a linear mixed-integer solver. We assess growth time in a facility in terms of its impact on survival (post-deployment) considering growth quantity requirements and growth facility production constraints. We explore the sensitivity of optimal facility number, location, and sizing to changes in the geographic distribution of demand and cost parameters computationally. Results show that the relationship between growth time and survival is critical to optimizing operational decisions for grown resources. These results inform the value of data certainty to optimize the logistics of coral aquaculture production.
生产栽培资源需要额外的规划，要考虑到生长时间。我们制定了一个数学规划模型，以确定生长设施的最佳位置和规模，这些设施受到资源存活率作为其生长时间函数的影响。我们的方法为关于设施的数量、位置和规模的战略决策以及在设施中培养资源的最佳生长时间的运营决策提供信息，以最小化总成本。我们使用两阶段算法和线性混合整数求解器，在大规模珊瑚礁修复的珊瑚养殖背景下解决设施选址和规模问题。我们根据生长数量要求和生长设施生产约束，评估设施内的生长时间对生存（部署后）的影响。我们从计算上探索了最优设施数量、位置和规模对需求和成本参数地理分布变化的敏感性。结果表明，生长时间和存活率之间的关系对优化生长资源的运营决策至关重要。这些结果说明了数据确定性对优化珊瑚养殖生产物流的价值。
