Developing a Robust Green Supply Chain Planning Optimization Model Considering Potential Risks

Al-Ashhab, M. S.

doi:10.21660/2020.73.52896

Cited by 8 publications

(4 citation statements)

References 34 publications

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“…This work is an extension of the work done in (4,12) . It entails the supply chain network's configuration and influence of performance considering the stated objectives (13) .…”

Section: Introductionmentioning

confidence: 89%

“…To reduce the environmental and economic impacts of supply chains in (4) , a singleitem comprehensive green supply chain planning optimization model is created. In (5) , a multi-objective, single-item, single-period optimization model in the strategic supply network planning process that includes the environmental investment decision is suggested.…”

Section: Introductionmentioning

confidence: 99%

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Developing a multi-item, multi-product, and multi-period supply chain planning optimization model

Al-Ashhab¹,

Mlybari²

2021

IJST

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“…This work is an extension of the work done in (4,12) . It entails the supply chain network's configuration and influence of performance considering the stated objectives (13) .…”

Section: Introductionmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Developing a multi-item, multi-product, and multi-period supply chain planning optimization model

Al-Ashhab¹,

Mlybari²

2021

IJST

Self Cite

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“…It takes about 45 days to make a round trip, during which a large number of greenhouse gases are emitted (Fig. 3) [3].…”

Section: Energy In Japanmentioning

confidence: 99%

Floating Automated Factory System for Effective Utilization of Seabed Resources and Reduction of Greenhouse Gas Emissions

Sato¹

2022

GEOMATE

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Japan has the sixth-largest Exclusive Economic Zone in the world, covering approximately 4.47 million square kilometers. Methane hydrate is known to exist under the seafloor, with approximately 100 times the amount of Japan's annual natural gas consumption. To minimize the cost from extraction to the processing of such seabed resources, the installation of facilities that can generate electricity directly above the sea area where the resources are located is considered the most efficient strategy for the extraction and conversion to energy. Furthermore, methane gas can be converted to hydrogen gas through a steam reforming process, thereby minimizing greenhouse gas emissions. By arranging various factories around the facility as floating structures, it will be possible to reduce the costs from product processing to the manufacturing of finished products. Further, floating factories can minimize tsunami damage when compared with factories on reclaimed land in the coastal areas. To effectively utilize energy resources and reduce greenhouse gas emissions, we propose a floating structure that can consolidate the respective movements of people, products, and logistics from the seafloor to the sea and its surroundings.

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“…Professional requirements are higher. However, the number of asset file attributes of general-purpose materials is small, and the ledger can be directly converted based on the purchase invoice [9][10].…”

Section: Differences In Measuring Materialsmentioning

confidence: 99%

Optimization of intelligent supply chain of metering materials based on data mining technology

song²,

Sun³

et al. 2022

Third International Conference on Computer Communication and Network Security (CCNS 2022)

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Metering asset equipment is an important basis for building a smart grid, and is mainly used for power metering at power supply terminals. Due to the big difference between the inventory management requirements of metering asset equipment and other materials of power supply enterprises, for example, it needs to be stored in special storage areas, warehouses and storage spaces. Therefore, it is usually necessary to use a dedicated inventory business for management. The main purpose of this paper is to optimize the intelligent supply chain of metering materials based on data mining technology. This paper mainly analyzes the organizational performance of the smart supply chain and the differences in metering materials. During the 10 iterations of the experiment, the maximum and average response times of the system gradually increased with the number of concurrent users. 1.965s and 1.224s, the maximum response time of which did not exceed the preset 3s target value, so the performance test passed.

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Developing a Robust Green Supply Chain Planning Optimization Model Considering Potential Risks

Cited by 8 publications

References 34 publications

Developing a multi-item, multi-product, and multi-period supply chain planning optimization model

Developing a multi-item, multi-product, and multi-period supply chain planning optimization model

Floating Automated Factory System for Effective Utilization of Seabed Resources and Reduction of Greenhouse Gas Emissions

Optimization of intelligent supply chain of metering materials based on data mining technology

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