A genetic algorithm for the fuzzy shortest path problem in a fuzzy network

Lü, Lin; Wu, Chuzheng; Ma, Liye

doi:10.1007/s40747-020-00195-8

Cited by 24 publications

(12 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, the performance of metaheuristics is often superior to that of traditional methods [6,48,56]. For instance, metaheuristics have been successfully applied to a wide range of fields, such as recommender systems, job scheduling, fake news stance detection, feature selection processes, fuzzy shortest paths, and electric vehicle routing [39,49,53,62,64,66]. Thus, a metaheuristic is adopted in the proposed framework to address the comprehensive ITP.…”

Section: Metaheuristicsmentioning

confidence: 99%

A metaheuristic-based framework for index tracking with practical constraints

Yuen¹,

Leung³

et al. 2021

Complex Intell. Syst.

View full text Add to dashboard Cite

Recently, numerous investors have shifted from active strategies to passive strategies because the passive strategy approach affords stable returns over the long term. Index tracking is a popular passive strategy. Over the preceding year, most researchers handled this problem via a two-step procedure. However, such a method is a suboptimal global-local optimization technique that frequently results in uncertainty and poor performance. This paper introduces a framework to address the comprehensive index tracking problem (IPT) with a joint approach based on metaheuristics. The purpose of this approach is to globally optimize this problem, where optimization is measured by the tracking error and excess return. Sparsity, weights, assets under management, transaction fees, the full share restriction, and investment risk diversification are considered in this problem. However, these restrictions increase the complexity of the problem and make it a nondeterministic polynomial-time-hard problem. Metaheuristics compose the principal process of the proposed framework, as they balance a desirable tradeoff between the computational resource utilization and the quality of the obtained solution. This framework enables the constructed model to fit future data and facilitates the application of various metaheuristics. Competitive results are achieved by the proposed metaheuristic-based framework in the presented simulation.

show abstract

Section: Metaheuristicsmentioning

confidence: 99%

A metaheuristic-based framework for index tracking with practical constraints

Yuen¹,

Leung³

et al. 2021

Complex Intell. Syst.

View full text Add to dashboard Cite

show abstract

“…Lin et al [24] proposed an efficient genetic algorithm to solve trapezoidal fuzzy shortest path problems (shortest path problems in which the traveling cost between every two nodes is represented by a trapezoidal fuzzy number).…”

Section: Literature Reviewmentioning

confidence: 99%

Mehar Approach for Finding Shortest Path in Supply Chain Network

et al. 2021

View full text Add to dashboard Cite

The aim of each company/industry is to provide a final product to customers at the minimum possible cost, as well as to protect the environment from degradation. Ensuring the shortest travel distance between involved locations plays an important role in achieving the company’s/industry’s objective as (i) the cost of a final product can be minimized by minimizing the total distance travelled (ii) finding the shortest distance between involved locations will require less fuel than the longest distance between involved locations. This will eventually result in lesser degradation of the environment. Hence, in the last few years, various algorithms have been proposed to solve different types of shortest path problems. A recently proposed algorithm for solving interval-valued Pythagorean fuzzy shortest path problems requires excessive computational efforts. Hence, to reduce the computational efforts, in this paper, firstly, an alternative lexicographic method is proposed for comparing interval-valued Pythagorean fuzzy numbers. Then, using the proposed lexicographic comparing method, a new approach (named as Mehar approach) is proposed to solve interval-valued Pythagorean fuzzy shortest path problems. Furthermore, the superiority of the proposed lexicographic comparing method, as well as the proposed Mehar approach, is discussed.

show abstract

“…Modern network science has progressed rapidly and has become an important research tool in sociology, computer science, biology, etc. [4,7,9,13,28,44]. The key to understanding the network is in-depth mining its intrinsic topology and finding the most represent backbone from a great number of complex connections.…”

Section: Introductionmentioning

confidence: 99%

Motif-h: a novel functional backbone extraction for directed networks

Bai

Fan

et al. 2021

Complex Intell. Syst.

View full text Add to dashboard Cite

Dense networks are very pervasive in social analytics, biometrics, communication, architecture, etc. Analyzing and visualizing such large-scale networks are significant challenges, which are generally met by reducing the redundancy on the level of nodes or edges. Motifs, patterns of the higher order organization compared with nodes and edges, are recently found to be the novel fundamental unit structures of complex networks. In this work, we proposed a novel motif h-backbone (Motif-h) method to extract functional cores of directed networks based on both motif strength and h-bridge. Compared with the state-of-the-art method Motif-DF and Entropy, our method solves two main issues which are often found in existing methods: the Motif-h reconsiders weak ties into our candidate set, and those weak ties often have critical functions of bridges in networks; moreover, our method provides a trade-off between the motif size and the edge strength, which quantifies the core edges accordingly. In the simulations, we compare our method with Motif-DF in four real-world networks and found that Motif-h can streamline the extraction of crucial structures compared with the others with limited edges.

show abstract

A genetic algorithm for the fuzzy shortest path problem in a fuzzy network

Cited by 24 publications

References 39 publications

A metaheuristic-based framework for index tracking with practical constraints

A metaheuristic-based framework for index tracking with practical constraints

Mehar Approach for Finding Shortest Path in Supply Chain Network

Motif-h: a novel functional backbone extraction for directed networks

Contact Info

Product

Resources

About