An Integrated Production-Distribution Planning Problem under Demand and Production Capacity Uncertainties: New Formulation and Case Study

被引:7
作者
Ben Abid, Taycir [1 ]
Ayadi, Omar [1 ]
Masmoudi, Faouzi [1 ]
机构
[1] Univ Sfax, Natl Engn Sch Sfax ENIS, Mech Modelling & Prod Res Lab LA2MP, Rd Soukra BP 1173-3038, Sfax, Tunisia
关键词
CHAIN NETWORK DESIGN; SUPPLY CHAIN; OPTIMIZATION; MODELS;
D O I
10.1155/2020/1520764
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this study, we propose to solve a biobjective tactical integrated production-distribution planning problem for a multisite, multiperiod, multiproduct, sea-air intermodal supply chain network under uncertainties. Two random parameters are considered simultaneously: product replenishment orders and production capacity, which are modelled via a finite set of scenarios, using a two-stage stochastic approach. A corresponding mathematical model is developed, coded, and solved using the LINGO 18.0 software optimisation tool. This model aims to simultaneously minimise the total costs of production in both regular and overtime, inventory, distribution, and backordering activities and maximise the customer satisfaction level over the tactical planning horizon. The AUGMECON technique is applied to handle with the multiobjective optimisation. The applicability and the performance of the proposed model are tested through a real-life case study inspired from a medium-sized Tunisian textile and apparel company. Sensitivity analysis on stochastic parameters and managerial insights for the studied supply chain network are argued based on the empirical findings.
引用
收藏
页数:15
相关论文
共 33 条
[1]   Robust Production Planning in Fashion Apparel Industry under Demand Uncertainty via Conditional Value at Risk [J].
Ait-Alla, Abderrahim ;
Teucke, Michael ;
Luetjen, Michael ;
Beheshti-Kashi, Samaneh ;
Karimi, Hamid Reza .
MATHEMATICAL PROBLEMS IN ENGINEERING, 2014, 2014
[2]   A Multiobjective Stochastic Production-Distribution Planning Problem in an Uncertain Environment Considering Risk and Workers Productivity [J].
Al-e-Hashem, S. M. J. Mirzapour ;
Baboli, A. ;
Sadjadi, S. J. ;
Aryanezhad, M. B. .
MATHEMATICAL PROBLEMS IN ENGINEERING, 2011, 2011
[3]   A multi-objective stochastic programming approach for supply chain design considering risk [J].
Azaron, A. ;
Brown, K. N. ;
Tarim, S. A. ;
Modarres, M. .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2008, 116 (01) :129-138
[4]   Fuzzy multi-objective optimization for multi-site integrated production and distribution planning in two echelon supply chain [J].
Badhotiya, Gaurav Kumar ;
Soni, Gunjan ;
Mittal, M. L. .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2019, 102 (1-4) :635-645
[5]   A two-stage stochastic programming approach for value-based closed-loop supply chain network design [J].
Badri, Hossein ;
Ghomi, S. M. T. Fatemi ;
Hejazi, Taha-Hossein .
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2017, 105 :1-17
[6]   Integrated supply chain planning under uncertainty using an improved stochastic approach [J].
Bidhandi, Hadi Mohammadi ;
Yusuff, Rosnah Mohd .
APPLIED MATHEMATICAL MODELLING, 2011, 35 (06) :2618-2630
[7]   MODELS AND MODEL VALUE IN STOCHASTIC-PROGRAMMING [J].
BIRGE, JR .
ANNALS OF OPERATIONS RESEARCH, 1995, 59 :1-18
[8]   Integrated Production and Outbound Distribution Scheduling: Review and Extensions [J].
Chen, Zhi-Long .
OPERATIONS RESEARCH, 2010, 58 (01) :130-148
[9]  
Coenen J., 2018, J CLEANER PRODUCTION, V40
[10]   LINEAR PROGRAMMING UNDER UNCERTAINTY [J].
Dantzig, George B. .
MANAGEMENT SCIENCE, 1955, 1 (3-4) :197-206