Product Modularization Using Cuckoo Search Algorithm

Wahdan, Hayam G.; Kassem, Sally; Abdelsalam, Hisham M.

doi:10.1007/978-3-319-53982-9_2

Cited by 6 publications

(6 citation statements)

References 18 publications

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“…The random walk via Lévy flight is used in the CS algorithm for a solution update process that effectively balances global and local search abilities 177,178 . The Lévy flight is more efficient in discovering the search space as its step length is much longer in the long run 179 …”

Section: Metaheuristic Algorithms In Iot Routing Protocolsmentioning

confidence: 99%

“…177,178 The Lévy flight is more efficient in discovering the search space as its step length is much longer in the long run. 179 Bello-Salau et al 180 have suggested two discretized variants of the CS algorithm, namely, random walk-based and levy flight-based, for efficient path finding in IoT-based VANETs. The exploration properties of the proposed approach have been improved by investigating the inverse mutation operator derived from the genetic algorithm.…”

Section: Cs-based Iot Routing Protocolsmentioning

confidence: 99%

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The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

Dong‐liang

Bei

Wang

2023

Int J Communication

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Summary Over the last decade, the Internet of Things (IoT) has become ever more popular, as is evident from its role in changing the human lifestyle and conferring remarkable privileges for them. It has a significant presence in various crucial areas, including smart cities, smart factories, manufacturing, transportation, and healthcare. Massive amounts of data generated by IoT devices have the potential to endanger the lifetime of nodes in IoT‐based networks due to increased communication power consumption. It has become crucial to propose solutions for network‐based issues, such as quality of service, security, network heterogeneity, congestion avoidance, reliable routing, and energy conservation. To address the mentioned problems, routing protocols play a critical role in data transmission among heterogeneous items. In such environments, routing refers to constructing routes between mobile nodes. Since identifying optimal routes among IoT nodes and establishing an effective routing protocol in an IoT network are an NP‐hard issue, employing metaheuristic algorithms may be a viable solution to overcome this problem. Various IoT routing protocols based on metaheuristic algorithms have been presented in recent years, but there is still a lack of systematic study for reviewing the existing works. The current study emphasizes the impact of metaheuristic algorithms in the IoT routing problem, discusses the optimization models, presents a comprehensive comparison of protocols based on critical parameters, and eventually suggests some hints for future studies.

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Section: Metaheuristic Algorithms In Iot Routing Protocolsmentioning

confidence: 99%

Section: Cs-based Iot Routing Protocolsmentioning

confidence: 99%

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

Dong‐liang

Bei

Wang

2023

Int J Communication

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“…DSM allows feedback, in addition to cyclic dependencies. This is one of the most important features of DSMs since many engineering applications possess that cyclic property [9].…”

Section: Design Structure Matrixmentioning

confidence: 99%

“…Cuckoo Search clustering algorithm is used to find the optimal number of clusters and the optimal assignment of components to clusters with total coordination cost as an objective [6,9]. Genetic clustering is proposed with Minimum Description Length measure.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Optimization Algorithm for Modular Product Design

Wahdan¹,

Abdelslam²,

Kassem³

2021

JESA

Self Cite

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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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“…This approach is applied on DSM to provide product architecting [23]. Cuckoo Search clustering algorithm is used to find the optimal number of clusters and the optimal assignment of components to clusters with total coordination cost as objective [24][25]. A new practical method is proposed, it is supports designers to create service modules by extending the DSM [26] developed reseach suggested a tradeoff between commonality and the quality of the modular architecture in product design platform selection also introduced a method for designers to identify multiple component sharing options that lie along a Pareto front of maximum commonality and strategic [27].…”

Section: Modular Designs With Functionality Objectivementioning

confidence: 99%

Sustainable Product Design Through Non-dominated Sorting Cuckoo Search

Wahdan¹,

Abdelslam²,

Abou-El-Enien³

et al. 2019

JESA

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Sustainability is an important consideration in product design. The sustainable design should fully consider the environmental, social, and economic factors of the product. However, the three factors are often conflicting with each other. This paper aims to strike a balance between these factors and achieve sustainable product design through multi-objective optimization. The three influencing factors of sustainability, namely, the environmental factor, social factor and economic factor, were respectively defined as environmental impact, labor time and labor cost. Then, the product to be designed was represented as a design structure matrix (DSM), a list of all product components and the dependency patterns among these components. On this basis, the non-dominated sorting and cuckoo search were combined into a multi-objective optimization technique to optimize the product functionality. This technique looks for a set of Pareto optimal solutions, each of which represents the structure of modules and the number of modules. The effectiveness of the proposed technique was verified through a case study on a coffee maker. The results show that our technique outperformed the previous optimization methods.

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Product Modularization Using Cuckoo Search Algorithm

Cited by 6 publications

References 18 publications

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

An Efficient Optimization Algorithm for Modular Product Design

Sustainable Product Design Through Non-dominated Sorting Cuckoo Search

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