Metaheuristic hybridizations for the regenerator placement and dimensioning problem in sub-wavelength switching optical networks

Pedrola, Oscar; Careglio, Davide; Klinkowski, Mirosław; Velasco, Luis; Bergman, Keren; Solé-Pareta, Josep

doi:10.1016/j.ejor.2012.08.011

Cited by 8 publications

(3 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The cost of regenerators in a network is measured in two main ways: (1) the number of regenerators placed in the network, and (2) the number of locations in which regenerators are placed ( Hartstein, Shalom, & Zaks, 2013 ). The second measure is the one that has been used in most of the research on the regenerator location problem (RLP) ( Chen, Ljubi ć, & Raghavan, 2010;Pedrola et al, 2013;Sen, Murthy, & Bandyopadhyay, 2008;Yetginer & Karasan, 2003 ). The RLP deals with a constraint on the geographical extent of signal transmission in the optical network design.…”

Section: Introductionmentioning

confidence: 99%

Regenerator location problem: Polyhedral study and effective branch-and-cut algorithms

Aneja

2017

European Journal of Operational Research

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Regenerator location problem: Polyhedral study and effective branch-and-cut algorithms

Aneja

2017

European Journal of Operational Research

View full text Add to dashboard Cite

“…According to Mishra et al, [81], among the optimization techniques that can be used for this purpose are linear programming and nonlinear programming. Alternative approaches such as GA have also been used to optimize products [82]. Therefore, based on previous studies, the selection of GA for design optimization is based on an undeniable heuristic algorithm.…”

Section: Product Designmentioning

confidence: 99%

A Review of Genetic Algorithm: Operations and Applications

Faizatulhaida Md Isa,

Wan Nor Munirah Ariffin,

Muhammad Shahar Jusoh

et al. 2024

ARASET

View full text Add to dashboard Cite

This article presents a review of the Genetic Algorithm (GA), a prominent optimization technique inspired by natural selection and genetics. In the context of rapidly evolving computational methodologies, GA have gained considerable attention for their efficacy in solving complex optimization problems across various domains. The background highlights the growing significance of optimization techniques in addressing real-world challenges. However, the inherent complexity and diversity of problems necessitate versatile approaches like GA. The problem statement underscores the need to explore the underlying operations and applications of GA to provide a nuanced understanding of their capabilities and limitations. The objectives of this review encompass delving into the fundamental genetic operators, such as selection, crossover, and mutation, while examining their role in maintaining diversity and converging toward optimal solutions. Methodology-wise, a systematic analysis of existing literature is undertaken to distil key insights and trends in GA applications. The main findings show the adaptability of GA in tackling problems spanning engineering, economics, bioinformatics, and beyond. By facilitating the discovery of optimal or near-optimal solutions within large solution spaces, GA proves its mettle in scenarios where traditional methods fall short. The conclusion underscores the enduring relevance of GA in the optimization landscape, emphasizing their potential to remain a pivotal tool for addressing intricate real-world challenges, provided their parameters are fine-tuned judiciously to balance exploration and exploitation.

show abstract

“…RPD aims at minimizing the number of costly, power-consuming optical-electrical-optical (O/E/O) signal regenerators. The contents of this chapter have been published in [28]. This work was done in collaboration with the NIT (Poland) and LRL at Columbia University (US).…”

Section: Thesis Contributions and Structurementioning

confidence: 99%

Cross-layer modeling and optimization of next-generation internet networks

Escribà¹

View full text Add to dashboard Cite

Scaling traditional telecommunication networks so that they are able to cope with the volume of future traffic demands and the stringent European Commission (EC) regulations on emissions would entail unaffordable investments. For this very reason, the design of an innovative ultra-high bandwidth power-efficient network architecture is nowadays a bold topic within the research community. So far, the independent evolution of network layers has resulted in isolated, and hence, far-from-optimal contributions, which have eventually led to the issues today's networks are facing such as inefficient energy strategy, limited network scalability and flexibility, reduced network manageability and increased overall network and customer services costs. Consequently, there is currently large consensus among network operators and the research community that cross-layer interaction and coordination is fundamental for the proper architectural design of next-generation Internet networks. This thesis actively contributes to the this goal by addressing the modeling, optimization and performance analysis of a set of potential technologies to be deployed in future cross-layer network architectures. By applying a transversal design approach (i.e., joint consideration of several network layers), we aim for achieving the maximization of the integration of the different network layers involved in each specific problem. To this end, Part I provides a comprehensive evaluation of optical transport networks (OTNs) based on layer 2 (L2) sub-wavelength switching (SWS) technologies, also taking into consideration the impact of physical layer impairments (PLIs) (L0 phenomena). Indeed, the recent and relevant advances in optical technologies have dramatically increased the impact that PLIs have on the optical signal quality, particularly in the context of SWS networks. Then, in Part II of the thesis, we present a set of case studies where it is shown that the application of operations research (OR) methodologies in the desing/planning stage of future cross-layer Internet network architectures leads to the successful joint optimization of key network performance indicators (KPIs) such as cost (i.e., CAPEX/OPEX), resources usage and energy consumption. OR can definitely play an important role by allowing network designers/architects to obtain good near-optimal solutions to real-sized problems within practical running times.

show abstract

Metaheuristic hybridizations for the regenerator placement and dimensioning problem in sub-wavelength switching optical networks

Cited by 8 publications

References 25 publications

Regenerator location problem: Polyhedral study and effective branch-and-cut algorithms

Regenerator location problem: Polyhedral study and effective branch-and-cut algorithms

A Review of Genetic Algorithm: Operations and Applications

Cross-layer modeling and optimization of next-generation internet networks

Contact Info

Product

Resources

About