Pareto-based algorithm for adaptive aggregate production and distribution planning in shrimp agroindustry supply chain

L. H. Machfud, E. Machfud
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Abstract

Intheglobalsupplychain,theintegrationofproductionanddistributionisoneoftheimportantactivitiesthatmust be carried out. This also applies to the shrimp agroindustry supply chain. The shrimp agroindustry is one of the agro-food industries that deals with processing raw shrimp into various frozen shrimp products. The demand for frozenshrimpproductsisverydiverse,whilethesupplyofrawshrimpconsistsofvarioussizesandhasperishable properties. To ful􀅭ill consumer demand, aggregate production planning must be made adaptively. Adaptive means being able to improve aggregate planning due to changes in demand. Integration of adaptive aggregate production and distribution planning will result in better planning. Based on this, we developed an adaptive aggregate production and distribution model for the shrimp agroindustry supply chain. Non-dominated Sorting Genetic Algorithm II (NSGA-II) which is a pareto-based algorithm is used to solve the problem. The aim is to minimize total costs and maximize service levels. The sample problem from the shrimp agroindustry in East Java is used to show the ef􀅭iciency of the proposed algorithm.
基于pareto算法的虾类农产品供应链自适应集料生产与分配规划
在全球供应链中,生产和分销的整合是必须进行的重要活动之一。这也适用于虾农工业供应链。虾农工业是将生虾加工成各种冷冻虾产品的农业食品工业之一。对冷冻虾产品的需求是非常多样化的,而虾的供应则是各种大小和易腐烂的特性。为了满足􀅭ill消费者需求,总生产计划必须自适应地制定。适应性意味着能够根据需求的变化改进总体规划。将适应性总体生产和分配计划相结合,将产生更好的计划。在此基础上,建立了虾农产业供应链的自适应集料生产与分配模型。非支配排序遗传算法II (non - dominant Sorting Genetic Algorithm II, NSGA-II)是一种基于pareto的算法。目标是最小化总成本和最大化服务水平。以东爪哇虾农工业为例,验证了该算法的有效性􀅭iciency。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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