Sustainable Product Design Through Non-dominated Sorting Cuckoo Search

Wahdan, Hayam G.; Abdelslam, Hisham; Abou-El-Enien, Tarek H. M.; Kassem, Sally

doi:10.18280/jesa.520502

Cited by 6 publications

(4 citation statements)

References 32 publications

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“…Literature has presented industrial clusters to obtain a competitive advantage and increase developments (Bialic-Davendra, 2011; Wahdan et al, 2019). For instance, Faller and Feldmüller (2015) have deliberated the methodology for optimizing and upgrading intellectual production in Germany’s small and medium enterprise (SME) clusters.…”

Section: Literature Reviewmentioning

confidence: 99%

An Empirical Analysis of Supply Chain Competitiveness and Cleaner Production

2022

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The increasing world population has placed tremendous pressure on global production systems, which has created a disjoint between the production and sustainability related goals of this sector. Several studies have confirmed this notion via Environmental Kuznets Curve, but this study envisages proposing a possible solution. It is hypothesized that competitive supply chain ecosystems (cluster development & production process sophistication) could help in reducing growth based CO2 emissions globally. An assessment of 135 countries between 2008 and 2018 is conducted. The estimates showed that the supply chain competitiveness has the potential in greenification of our production systems. Here indicators like value chain breadth and cluster development can reduce the CO2 emissions at each production level. Further regions from the geographic map, like North America and Asia Pacific, can adopt a green supply chain from other regions.

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Section: Literature Reviewmentioning

confidence: 99%

An Empirical Analysis of Supply Chain Competitiveness and Cleaner Production

2022

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“…The problem has set of conflicting objectives, product functionality objective, labor time, environmental impact and labor cost. [28].…”

Section: Related Workmentioning

confidence: 99%

An Efficient Optimization Algorithm for Modular Product Design

Wahdan¹,

Abdelslam²,

Kassem³

2021

JESA

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Modularity concepts play an important role in the process of developing new complex products. Modularization involves dividing a product into a set of modules - each of which consisting of a set of components - that are interdependent in the same cluster and independent between clusters. During this process, a product can be represented using a Design Structure Matrix (DSM). A DSM acts as a tool for system analysis to provide clear visualization of product elements. In addition, DSM, shows the interactions between these product elements. This paper aims to propose an efficient optimization algorithm that dynamically divides a DSM into an optimal number and size of clusters in a way that minimizes total coordination cost; the interactions inside clusters (modules) and interactions between clusters. Given problem complexity, five metaheuristic optimization algorithms are proposed and tested to solve it; these algorithms are used to determine: (1) the optimal clusters’ number within a DSM, and (2) the optimal components assignment clusters to minimize the total coordination cost. The five used metaheuristics are: Cuckoo Search, Modified Cuckoo Search, Particle Swarm Optimization, Simulated Annealing, and Gravitational Search Algorithm. Eighty problems with different properties are generated and used to examine the proposed algorithms for effectiveness and efficiency. Extensive comparisons are conducted and analyzed. Cuckoo Search is outperforming the other four algorithms.

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“…Some scholars have defined world-class industrial clusters from the perspective of obtaining competitive advantages and realizing world-class manufacturing [9,10]. For example, Faller and Feldmüller [11] studied the method to optimize and upgrade the intelligent manufacturing in clusters of small and medium enterprises (SMEs) in Germany.…”

Section: Intelligent Manufacturing Clustermentioning

confidence: 99%

Multi-agent Modeling of the Collaborative Operation of the Producer Service Supply Chain under the Intelligent Manufacturing Clusters in the Yangtze River Delta

Liu¹

2020

JESA

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With the proliferation and aggregation of advanced production technology and information technology, several regional intelligent manufacturing clusters have taken shape in China. The development of intelligent manufacturing, which is highly technical, innovative, and informatized, needs the support of more professional producer services. Considering the broad scope of producer service supply-demand in regional intelligent manufacturing, this paper takes the intelligent manufacturing cluster in the Yangtze River Delta as the object, analyzes the limited access to producer services required for production operations, and proposes to integrate and supply the resources of multiple service agents in the region in a dynamic and collaborative manner. Then, the Multi-Agent model was constructed for the producer service supply chain, and the relevant factor libraries and decision libraries were designed. Finally, an empirical analysis was carried out to evaluate the stability of the collaborative operation of the producer service supply chain under the effect of some collaboration factors. The results show that the model has a certain theoretical reference value.

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Sustainable Product Design Through Non-dominated Sorting Cuckoo Search

Cited by 6 publications

References 32 publications

An Empirical Analysis of Supply Chain Competitiveness and Cleaner Production

An Empirical Analysis of Supply Chain Competitiveness and Cleaner Production

An Efficient Optimization Algorithm for Modular Product Design

Multi-agent Modeling of the Collaborative Operation of the Producer Service Supply Chain under the Intelligent Manufacturing Clusters in the Yangtze River Delta

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