A deterministic and nature-inspired algorithm for the fuzzy multi-objective path optimization problem

Ma, Yiming; Hu, Xiao-Bing; Zhou, Huicheng

doi:10.1007/s40747-022-00825-3

Cited by 4 publications

(1 citation statement)

References 48 publications

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“…The auxiliary problem consists of the calculation of the efficient paths set of a MOSPP, based on the order relation between fuzzy numbers referred to above. Other variants of this problem have been approached in [140,141]. Paper [137] deals with a multiobjective path problem in a directed network, and the associated arc weights are represented as rough variables in order to model the imprecision.…”

Section: (B) Imprecision In Shortest Path Problemsmentioning

confidence: 99%

Multiobjective Path Problems and Algorithms in Telecommunication Network Design—Overview and Trends

Craveirinha,

Clímaco,

Girão-Silva

et al. 2024

Algorithms

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A major area of application of multiobjective path problems and resolution algorithms is telecommunication network routing design, taking into account the extremely rapid technological and service evolutions. The need for explicit consideration of heterogeneous Quality of Service metrics makes it advantageous for the development of routing models where various technical–economic aspects, often conflicting, should be tackled. Our work is focused on multiobjective path problem formulations and resolution methods and their applications to routing methods. We review basic concepts and present main formulations of multiobjective path problems, considering different types of objective functions. We outline the different types of resolution methods for these problems, including a classification and overview of relevant algorithms concerning different types of problems. Afterwards, we outline background concepts on routing models and present an overview of selected papers considered as representative of different types of applications of multiobjective path problem formulations and algorithms. A broad characterization of major types of path problems relevant in this context is shown regarding the overview of contributions in different technological and architectural network environments. Finally, we outline research trends in this area, in relation to recent technological evolutions in communication networks.

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Section: (B) Imprecision In Shortest Path Problemsmentioning

confidence: 99%

Multiobjective Path Problems and Algorithms in Telecommunication Network Design—Overview and Trends

Craveirinha,

Clímaco,

Girão-Silva

et al. 2024

Algorithms

View full text Add to dashboard Cite

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A practical type-3 Fuzzy control for mobile robots: predictive and Boltzmann-based learning

Alkabaa,

Taylan,

Balubaid

et al. 2023

Complex Intell. Syst.

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This study presents an innovative path-following scheme using a new intelligent type-3 fuzzy system for mobile robots. By designing a non-singleton FS and incorporating error measurement signals, this system is able to handle natural disturbances and dynamics uncertainties. To further enhance accuracy, a Boltzmann machine (BM) models tracking errors and predicts compensators. A parallel supervisor is also included in the central controller to ensure robustness. The BM model is trained using contrastive divergence, while adaptive rules extracted from a stability theorem train the NT3FS. Simulation results using chaotic reference signals show that the proposed scheme is accurate and robust, even in the face of unknown dynamics and disturbances. Moreover, a practical implementation on a real-world robot proves the feasibility of the designed controller. To watch a short video of the scheme in action, visit shorturl.at/imoCH.

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SRNN-RSA: a new method to solving time-dependent shortest path problems based on structural recurrent neural network and ripple spreading algorithm

Yu,

Song

2024

Complex Intell. Syst.

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Influenced by external factors, the speed of vehicles in the traffic network is changing all the time, which makes the traditional static shortest route unable to meet the real logistics distribution needs. Considering that the existing research on time-dependent shortest path problems (TDSPP) do not include the topological information of the traffic network, it is unable to reflect the spatial and temporal dynamic characteristics of the traffic network during the vehicle travelling process and is unable to update to the changes of the vehicle speed in real time, and poor scalability. Therefore, we used the structural RNN (SRNN) model containing topological information of the road network is used to predict time-varying speeds in the traffic road network. We proposed an SRNN-RSA framework for solving the TDSPP problem, which achieves a synergistic evolution between the real-time vehicle speed change process and the RSA solving process, and the scalability of the proposed SRNN-RSA is demonstrated and validated using different real data. Compared with other algorithms, the results show that SRNN-RSA has the lowest error with the actual situation, which can balance the solution accuracy and calculation speed and is more consistent with the real traffic road network, with better stability and expandability.

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A deterministic and nature-inspired algorithm for the fuzzy multi-objective path optimization problem

Cited by 4 publications

References 48 publications

Multiobjective Path Problems and Algorithms in Telecommunication Network Design—Overview and Trends

Multiobjective Path Problems and Algorithms in Telecommunication Network Design—Overview and Trends

A practical type-3 Fuzzy control for mobile robots: predictive and Boltzmann-based learning

SRNN-RSA: a new method to solving time-dependent shortest path problems based on structural recurrent neural network and ripple spreading algorithm

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