A risk-averse two-stage stochastic programming model for a joint multi-item capacitated line balancing and lot-sizing problem

被引：15

作者：

Li, Yuchen ^{[1
]}

Saldanha-da-Gama, Francisco ^{[2
,3
]}

Liu, Ming ^{[4
]}

Yang, Zaoli ^{[1
]}

机构：

[1] Beijing Univ Technol, Sch Econ & Management, Beijing, Peoples R China

[2] Univ Lisbon, Dept Estat & Invest Operac, Fac Ciencias, Lisbon, Portugal

[3] Univ Lisbon, Ctr Matemat, Aplicacoes Fundamentais & Invest Operac, Fac Ciencias, Lisbon, Portugal

[4] Tongji Univ, Sch Econ & Management, Shanghai, Peoples R China

来源：

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH | 2023年 / 304卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Combinatorial optimization; COVID-19; Assembly line balancing; Lot; -sizing; Uncertain demand; CONDITIONAL VALUE; ASSEMBLY LINES; PLANNING-MODEL; DEMAND; OPTIMIZATION; CONSTRAINTS; FORMULATION;

D O I：

10.1016/j.ejor.2021.09.043

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

In this paper, a comprehensive production planning problem under uncertain demand is investigated. The problem intertwines two NP-hard optimization problems: an assembly line balancing problem and a capacitated lot-sizing problem. The problem is modelled as a two-stage stochastic program assuming a risk-averse decision maker. Efficient solution procedures are proposed for tackling the problem. A case study related to mask production is presented. Several insights are provided stemming from the COVID-19 pandemic. Finally, the results of a series of computational tests are reported. (c) 2021 Elsevier B.V. All rights reserved.

引用

页码：353 / 365

页数：13

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