Comparison of Genetic and Gradient Descent Algorithms for Determining Fuzzy Measures

Alavi, S. H.; Jassbi, Javad; Serra, P.; Ribeiro, Rita A.

doi:10.1109/ines.2006.1689357

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…During the past two decades, GAs have been successfully and broadly applied to solve constrained optimization problems. 26 Hong et al 27 observed that in most GA variants only crossover and mutation operators are employed in each generation. As a result, the search ability of these algorithms could be limited.…”

Section: Algorithm Designmentioning

confidence: 99%

Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks

Liu

2018

International Journal of Distributed Sensor Networks

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Delay-tolerant networks are novel wireless mobile networks, which are characterized with high latency and frequent disconnectivity. Besides, people carrying mobile devices form a lot of communities because of similar interests and social relationships. How to improve the routing efficiency in multi-community scenarios has become one of the research hot spots in delay-tolerant networks. In this article, we present a network model of the multi-community delay-tolerant networks and formulate a dynamic quota-controlled routing problem of minimizing the average number of copies of a message that satisfies the required delivery probability under the given time-to-live of the message as a nonlinear optimization problem. To solve this problem, we propose an improved genetic algorithm called genetic algorithm for delivery probability and time-to-live optimization for the dynamic quota-controlled routing scheme to reduce the routing cost further. In addition, a cost-efficient dynamic quota-controlled routing protocol based on genetic algorithm for delivery probability and time-to-live optimization is proposed, which can dynamically adjust message copies according to its assigned delivery probability and time-to-live in different communities on the shortest path. Both the numerical and simulation results show that our routing with the proposed algorithm is more cost efficient.

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Section: Algorithm Designmentioning

confidence: 99%

Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks

Liu

2018

International Journal of Distributed Sensor Networks

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“…Notice that for n attributes, 2 n − 2 coefficients are needed to specify the model. Regarding the alternatives for fuzzy measure identification [8,5,6,7], we will focus on the HLMS algorithm [9] and its convergence. In particular, a study of the HLMS learning rate parameter and its correct setting for HLMS convergence is presented.…”

Section: Introductionmentioning

confidence: 99%

On the convergence of HLMS Algorithm

Murillo¹,

Guillaume²,

Tapia³

et al. 2011

Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011)

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In multicriteria decision making, the study of attribute contributions is crucial to attain correct decisions. Fuzzy measures allow a complete description of the joint behavior of attribute subsets. However, the determination of fuzzy measures is often hard. A common way to identify fuzzy measures is HLMS (Heuristic Least Mean Squares) algorithm. In this paper, the convergence of the HLMS algorithm is analyzed. First, we show that the learning rate parameter (α) dominates the convergence of HLMS. Second, we provide an upper bound for α that guarantees HLMS convergence. In addition, a toy example shows the descriptive power of fuzzy measures versus the poverty of individual measures.

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Revised HLMS: A useful algorithm for fuzzy measure identification

Murillo

Guillaume²,

Tapia

et al. 2013

Information Fusion

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An important limitation of fuzzy integrals for information fusion is the exponential growth of coefficients for an increasing number of information sources. To overcome this problem a variety of fuzzy measure identification algorithms has been proposed. HLMS is a simple gradient-based algorithm for fuzzy measure identification which suffers from some convergence problems. In this paper, two proposals for HLMS convergence improvement are presented, a modified formula for coefficients update and new policy for monotonicity check. A comprehensive experimental work shows that these proposals indeed contribute to HLMS convergence, accuracy and robustness.

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Comparison of Genetic and Gradient Descent Algorithms for Determining Fuzzy Measures

Cited by 3 publications

References 12 publications

Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks

Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks

On the convergence of HLMS Algorithm

Revised HLMS: A useful algorithm for fuzzy measure identification

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