A new algorithm for the discrete fuzzy shortest path problem in a network

Chuang, Tzung-Nan; Kung, Jung-Yuan

doi:10.1016/j.amc.2005.04.097

Cited by 36 publications

(17 citation statements)

References 15 publications

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“…Okada [14,15] based on the possibility theory, introduced the concept of ''degree of possibility'' for the fuzzy arc lengths. Chuang et al [16,17] proposed a new algorithm for the discrete fuzzy shortest path problem in a network. Hernandesa [18] proposed an iterative algorithm that assumes a generic ranking index for comparing the fuzzy numbers.…”

Section: Introductionmentioning

confidence: 99%

A new fuzzy neural network model for solving fuzzy linear programming problems and its applications

Effati

Pakdaman

Ranjbar

2010

Neural Comput & Applic

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This paper is concentrated on two types of fuzzy linear programming problems. First type with fuzzy coefficients in the objective function and the second type with fuzzy right-hand side values and fuzzy variables. Considering fuzzy derivative and fuzzy differential equations, these kinds of problems are solved using a fuzzy neural network model. To show the applicability of the method, it is applied to solve the fuzzy shortest path problem and the fuzzy maximum flow problem. Numerical results illustrate the method accuracy and it's simple implementation.

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Section: Introductionmentioning

confidence: 99%

A new fuzzy neural network model for solving fuzzy linear programming problems and its applications

Effati

Pakdaman

Ranjbar

2010

Neural Comput & Applic

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“…Chuang and Kung (2005) proposed a heuristic procedure to find the FSP length among all possible paths in a network. Chuang and Kung (2006) proposed a new algorithm that obtains the FSP length and the corresponding SP in a discrete FSP problem. Hernandes et al (2007) considered a genetic algorithm (GA) for solving FSP problems where the decision maker can choose a ranking index that best suits the problem.…”

Section: Introductionmentioning

confidence: 99%

A novel artificial bee colony algorithm for shortest path problems with fuzzy arc weights

2016

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“…are naturally imprecise for most practical applications. In such cases, an appropriate modeling approach may justifiably make use of fuzzy numbers, and so does the name fuzzy shortest path problem (FSPP) appear in the literature [1,3,2,23] [12] [11] [27]. Since it involves the addition and the comparison between fuzzy numbers (particularly triangular fuzzy numbers), the FSPP is very different from the conventional SPP, which involves only real numbers.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy TOPSIS approach for finding shortest path in multimodal transportation networks

Yamani¹,

Mouncif²,

Rida³

2014

ijco

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The paper must have abstract. In this paper, we present a fuzzy shortest path algorithm in Multimodal Transportation Networks (MTN). To extend the classical problem of shortest path, an innovative framework is presented, which integrates Fuzzy Logic and Multi Criteria Decision Making (MCDM) techniques. The aim is to deal with an efficient design for the multimodal shortest path computation taking into accounts not only the expected travel time, but also additional constraints such as: delays at mode and arc switching points, costs, viability of the sequence of the used modes and the number of modal transfers. To this scope, all previously mentioned constraints are evaluated following a new approach based on Fuzzy Logic and aggregated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to find the shortest path in MTN. A numerical example is also presented to demonstrate the computational process of the proposed approach.

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A new algorithm for the discrete fuzzy shortest path problem in a network

Cited by 36 publications

References 15 publications

A new fuzzy neural network model for solving fuzzy linear programming problems and its applications

A new fuzzy neural network model for solving fuzzy linear programming problems and its applications

A novel artificial bee colony algorithm for shortest path problems with fuzzy arc weights

A fuzzy TOPSIS approach for finding shortest path in multimodal transportation networks

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