A system dynamics model for dynamic capacity planning of remanufacturing in closed-loop supply chains

Vlachos, Dimitrios; Georgiadis, Patroklos; Iakovou, Eleftherios

doi:10.1016/j.cor.2005.03.005

Cited by 348 publications

(188 citation statements)

References 9 publications

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“…The impact of various policy scenarios, is analyzed by Vlachos et al (2007), who derive their results from a general system dynamics model of a closed-loop supply chain. Also using the system dynamics approach, Georgiadis (2013) specifically focused on issues concerning the paper industry.…”

Section: Related Workmentioning

confidence: 99%

On stabilizing volatile product returns

Nowak

Hofer

2014

European Journal of Operational Research

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Section: Related Workmentioning

confidence: 99%

On stabilizing volatile product returns

Nowak

Hofer

2014

European Journal of Operational Research

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“…Level variables represent stocks in system dynamic models 14,15 . This means that all the Level variables in the model, namely, Population, GDP, Capacity under Construction, and Grid Generation Capacity are stock operating the Principle of Accumulation 3 , and take on the form of Equation (1) to run in the model.…”

Section: Brief Description Of Model Workingsmentioning

confidence: 99%

“…Stocks are accumulations of anything that can be counted, give systems inertia and provide them with memory. Delays are created in stocks through accumulating the difference between inflow and outflow 14,15 .…”

Section: System Dynamics Modellingmentioning

confidence: 99%

“…At least two negative feedback loops, or correcting loops exist in a system [13][14][15]22 ; the first is what controls the inflow, and the second, controls the outflow. Either or both can be used to bring the system to a desired level.…”

Section: Data Collectionmentioning

confidence: 99%

“…They seek to grow exponentially forever, and since no quantity can grow forever, there must be limits to growth. The self-correcting loops or negative (balancing) feedback are what limit growth as they counteract change [13][14][15] . Further description of how loops work in SDM is given in Bitok-Kivuti, Momodu and Pokhariyal 16 .…”

Section: System Dynamics Modellingmentioning

confidence: 99%

See 2 more Smart Citations

System dynamic modelling of electricity planning and climate change in West Africa

Momodu¹,

Kivuti-Bitok²

2018

AAS Open Res

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It is imperative to develop an efficient strategic approach to Background managing the push-pull factor in economic development, particularly as relates to climate change and energy interactions in the West African Region. This article demonstrates the use of System Dynamics Modelling (SDM) for that purpose; to manage the development of energy growth with reduced impact in regards to climate change. The complexities of energy planning in relation to climate change necessitates the need for the tool to examine low carbon economy mixed with traditional approaches of planning.: Vensim DSS version 6.2 was used to develop the model. WAPP Methods member country level data elicited from WAPP and ECOWAS Regional Electricity Regulatory Authority (ERERA) serves as the set of basic data used to develop and run the main model. These were complemented with other data elicited from various journal articles and internet sources. These include population and its average growth rate, GDP, per capita income, average per capita electricity demand, electricity generated, average electricity tariff, generation technology type, amongst others.: SDM demonstrates the capability to understand the theoretical frame Results for trade-offs between economic development and climate change, by handling the nonlinear relationship between generation adequacy and greenhouse gas (GHG) emission reduction for better targeted strategic regional intervention on climate change.: The primary goal of this paper was to demonstrate the use of Conclusion SDM to aid in resource planning in an inexpensive way to examine low carbon pathway. With the SDM, the goal of low carbon pathway in the energy system was achieved without the cost of controlled trials.

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