Coupling Soft Computing, Simulation and Optimization in Supply Chain Applications: Review and Taxonomy

Raoui, Hanane El; Oudani, Mustapha; Alaoui, A. El

doi:10.1109/access.2020.2973329

Cited by 22 publications

(8 citation statements)

References 114 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Three typical SBO approaches are discrete-event simulation, agent-based, and system dynamics. However, fewer studies exist on the simulation of transportation disruption during pandemic crises, with an increasing need to explore this research area (Dolgui & Ivanov, 2021 ; El Raoui et al, 2020 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…1. Clusters 1 and 2 dealt with the SC dynamics and resilience, which connect the ripple effect with simulation as a solution strategy (El Raoui et al, 2020;Ivanov, 2019;Rozhkov et al, 2022), while clusters 3 and 4 represented the SC portfolio and risk management with optimization as a solution strategy (Ivanov 2021a;Song et al, 2022).…”

Section: Present Status Of Literaturementioning

confidence: 99%

See 1 more Smart Citation

RETRACTED ARTICLE: Responsive strategies for new normal cold supply chain using greenfield, network optimization, and simulation analysis

et al. 2023

View full text Add to dashboard Cite

The global–local supply chains are affected by the forward and downward propagation of COVID-19. The pandemic disruption is a low-frequency and high-impact (black swan) event. Adapting to the “New Normal” situation requires adequate risk mitigation strategies. This study proposes a methodology to implement a risk mitigation strategy during supply chain disruptions. Random demand accumulation strategies are considered to identify the disruption-driven challenges under different pre and post-disruption scenarios. The best mitigation strategy and the optimal location of distribution centers to maximize the overall profit were determined using simulation-based optimization, greenfield analysis, and network optimization techniques. The proposed model is then evaluated and validated using appropriate sensitivity analysis. The main contribution of the study is to (i) perform cluster-based supply chain disruption analysis, (ii) propose a resilient and flexible model to illustrate the proactive and reactive measures for the ripple effect, (iii) prepare the supply chain for future pandemic-like crises, and (v) reveal the relationship between the pandemic impact and supply chain resilience. A case study of an ice cream manufacturer is used to demonstrate the proposed model.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Present Status Of Literaturementioning

confidence: 99%

RETRACTED ARTICLE: Responsive strategies for new normal cold supply chain using greenfield, network optimization, and simulation analysis

et al. 2023

View full text Add to dashboard Cite

show abstract

“…There is a big difference between the warehousing management of measurement assets and the company's general material warehousing management [7][8], mainly including the following aspects:…”

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)

View full text Add to dashboard Cite

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.

show abstract

“…Moreover, supply networks become more and more complex and large-scale with the increasing development of lean manufacturing and economic globalization. Thousands of firms reciprocally depend on each other to form a complex system [2].…”

Section: Introductionmentioning

confidence: 99%

Memetic Algorithm With Local Neighborhood Search for Bottleneck Supplier Identification in Supply Networks

2020

View full text Add to dashboard Cite

With the development of lean manufacturing and economic globalization, supply networks increasingly become complex and large-scale, within which thousands of firms inter-depend with each other. Due to these increasing inter-dependencies, disruption of a quite few critical suppliers, namely bottleneck suppliers, can induce high loss to a supply network and even make the whole network dysfunction. Identification of bottleneck suppliers is significantly important for supply network risk management. Thus, in this paper, a method based on a memetic algorithm with local neighborhood search (MALNS) is proposed to identify bottleneck suppliers in a two-stage supply network. Firstly, a model based on multipartite network is designed to describe the product supply-demand relations between multiple manufacturers and suppliers, which considers the different roles of manufacturer and supplier and differentiates the products that suppliers supply. To assess the loss caused by supplier disruptions, two performance metrics of supply networks, average product availability rate and manufacturer functioning rate, are presented. Then, a MALNS-based method is proposed to identify bottleneck suppliers, i.e., suppliers whose disruption will decrease both performance metrics most greatly. Finally, a case study based on a real automobile supply network is presented to validate the applicability and effectiveness of the proposed method.

show abstract

Coupling Soft Computing, Simulation and Optimization in Supply Chain Applications: Review and Taxonomy

Cited by 22 publications

References 114 publications

RETRACTED ARTICLE: Responsive strategies for new normal cold supply chain using greenfield, network optimization, and simulation analysis

RETRACTED ARTICLE: Responsive strategies for new normal cold supply chain using greenfield, network optimization, and simulation analysis

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

Memetic Algorithm With Local Neighborhood Search for Bottleneck Supplier Identification in Supply Networks

Contact Info

Product

Resources

About