Multi-stage multi-product multi-period production planning with sequence-dependent setups in closed-loop supply chain

2017 ◽  
Vol 113 ◽  
pp. 602-613 ◽  
Author(s):  
S. Torkaman ◽  
S.M.T Fatemi Ghomi ◽  
B. Karimi
Keyword(s):  
Supply Chain ◽  
Production Planning ◽  
Closed Loop ◽  
Closed Loop Supply Chain ◽  
Sequence Dependent ◽  
Multi Stage

Multi-objective robust optimization for multi-stage-multi-product agile closed-loop supply chain under uncertainty in the context of circular economy

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saeid Jafarzadeh Ghoushchi ◽  
Iman Hushyar ◽  
Kamyar Sabri-Laghaie
Keyword(s):  
Supply Chain ◽  
Robust Optimization ◽  
Circular Economy ◽  
Closed Loop ◽  
Mixed Integer ◽  
Closed Loop Supply Chain ◽  
Content Type ◽  
Multi Objective ◽  
Multi Stage ◽  
Proposed Model

PurposeA circular economy (CE) is an economic system that tries to eliminate waste and continually use resources. Due to growing environmental concerns, supply chain (SC) design should be based on the CE considerations. In addition, responding and satisfying customers are the challenges managers constantly encounter. This study aims to improve the design of an agile closed-loop supply chain (CLSC) from the CE point of view.Design/methodology/approachIn this research, a new multi-stage, multi-product and multi-period design of a CLSC network under uncertainty is proposed that aligns with the goals of CE and SC participants. Recycling of goods is an important part of the CLSC. Therefore, a multi-objective mixed-integer linear programming model (MILP) is proposed to formulate the problem. Besides, a robust counterpart of multi-objective MILP is offered based on robust optimization to cope with the uncertainty of parameters. Finally, the proposed model is solved using the e-constraint method.FindingsThe proposed model aims to provide the strategic choice of economic order to the suppliers and third-party logistic companies. The present study, which is carried out using a numerical example and sensitivity analysis, provides a robust model and solution methodology that are effective and applicable in CE-related problems.Practical implicationsThis study shows how all upstream and downstream units of the SC network must work integrated to meet customer needs considering the CE context.Originality/valueThe main goal of the CE is to optimize resources, reduce the use of raw materials, and revitalize waste by recycling. In this study, a comprehensive model that can consider both SC design and CE necessities is developed that considers all SC participants.

Modeling and Analysis of a Closed-Loop Supply Chain in Consideration of Extra Demand

2018 ◽  
Vol 12 (4) ◽  
pp. 469-481
Author(s):  
Ayako Okuda ◽  
Aya Ishigaki ◽  
Tetsuo Yamada ◽  
Surendra M. Gupta ◽  
◽  
...  
Keyword(s):  
Supply Chain ◽  
Production Planning ◽  
Closed Loop ◽  
Chain Model ◽  
Manufacturing Companies ◽  
Closed Loop Supply Chain ◽  
Modeling And Analysis ◽  
Supply Chain Model ◽  
Manufactured Products ◽  
Demand Fluctuations

In recent years, activities undertaken to reduce environmental impacts – such as recycling and reusing – have been increasing in popularity. For manufacturing companies, designing and using a closed-loop supply chain can help meet social responsibility objectives and enhance competitiveness. A closed-loop supply chain requires the accurate prediction of not only demand but also returned products; however, in the literature, the quantity of returned products is assumed to be dependent on demand. Importantly, the quantity of returned products is influenced by past demand and use periods. Further, some returned products may be treated as end-of-life products, because of quality deterioration. The purpose of this study is to design a closed-loop supply chain model in the context of returned product quantities as affected by past demand, use period, and extra demand, in order to analyze system performance. Herein, the quantity of demand influences the quantity of returned products, and hence the quantity of reusable products. Moreover, the dynamics of returned products, demand, and reusable products will also significantly influence production planning. In this study, fluctuations in the quantity of returned products influence not only production planning but also future demand fluctuations. The results of numerical examples derived from using the model proposed in this study clarify that the quantities of reusable products and manufactured products will fluctuate depending on the return rate, given policies that prioritize the sale of reusable products. This finding suggests that manufacturers need to consider reducing their environmental impact as well as establishing production planning and inventory control policies that contain fluctuations in the quantities of reusable and manufactured products.

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