New product supply chain configuration with fuzzy parameters

Author(s):  
Jihui Zhang ◽  
Guijuan Chang ◽  
Junqin Xu
2017 ◽  
Vol 16 (04) ◽  
pp. 291-315 ◽  
Author(s):  
Imane Ballouki ◽  
Mohammed Douimi ◽  
Latifa Ouzizi

In the decline phase of product lifecycle, industrials need to re-design their products to introduce new functions and/or customers’ new preferences. These changes may not only affect the product’s bill of material, but also its supply chain network. Consequently, new supply chain costs are generated. This paper addresses the problem of supply chain configuration considering new product re-design using a multi-agent system (MAS). The objective of the system is to ensure good collaboration between two different points of view, supply chain partners and product designers, to make better decisions. To model the proposed system, we select the multi-agent system engineering (MaSe) methodology. The MAS framework contains three types of agents, namely, “product design agent” and “supply chain agents” which are fitted with optimization tools. These tools allow costs’ optimization and selection of supply chain means (suppliers, technologies, etc.). Finally, the system contains a “communication agent” acting like a mediator; it facilitates data exchange between designers. To support distributed decision-making, two models of mixed integer linear programming are adopted and implemented within the framework for supply chain optimization. The overall MAS approach was tested in simulation with a case study. The objective of the simulation is to choose among three product alternatives the cheapest one based on its supplying and production costs, under capacity constraints. The MAS was able to find the best product alternative among three alternatives proposed by product design team and select optimal supply chain means. The optimal supply chain contains two suppliers: one machine and one subcontractor to satisfy customer’s demand.


2018 ◽  
Vol 29 (6) ◽  
pp. 1002-1025 ◽  
Author(s):  
Remica Aggarwal

Purpose Green supply chain management and new product innovation and diffusion have become quite popular and act as a rich source of providing competitive advantage for companies to trade without further deteriorating environmental quality. However, research on low-carbon footprint supply chain configuration for a new product represents a comparably new trend and needs to be explored further. Using relatively simple models, the purpose of this paper is to demonstrate how carbon emissions concerns, such as carbon emission caps and carbon tax scheme, could be integrated into an operational decision, such as product procurement, production, storage and transportation concerning new fast-moving consumer goods (FMCG) product introduction. Design/methodology/approach The situation titled “low-carbon footprint supply chain configuration problems” is mathematically formulated as a multi-objective optimization problem under the dynamic and stochastic phenomenon concerning receiver’s demand requirements and production plant capacity constraints. Further, the effects of demand and capacities’ uncertainties are modeled using the chance constraint approach proposed by Charnes and Cooper (1959, 1963). Findings Various cases have been validated using the case example of a new FMCG product manufacturer. To validate the proposed models, data are generated randomly and solved using optimization software LINGO 10.0. Originality/value The attempt is novel in the context of considering the dynamic and stochastic phenomenon with respect to demand center’s requirements and manufacturing plant’s capacity constraints with regard to the low-carbon footprints supply chain configuration of a new FMCG product.


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