An algorithmic approach for finding the fuzzy constrained shortest paths in a fuzzy graph

Liao, Xiaoqun; Wang, Jiayi; Ma, Liye

doi:10.1007/s40747-020-00143-6

Cited by 10 publications

(5 citation statements)

References 35 publications

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“…As shown in Table 2, the shortest path for 5 nodes, the shortest path of nodes no. (6,11,12,13,19,23,26) are also matched with what is shown in the table. For instance, the shortest path between node 6 and node 50 was 6-23-50, which can prove that the algorithm finds the best value of the objective function.…”

Section: Resultssupporting

confidence: 59%

“…Sori et al [18] present a fuzzy inference system to find the shortest path with three objectives and one constraint on the hop count, the multi-objective are the cost, time, and risk, which can be considered as corresponding to cost, delay, and interference. Liao et al [19] used LINGO software to solve a constrained shortest path problem. Their objective is to find the path with the minimum cost where delay time does not more than a predetermined delay time.…”

Section: Related Workmentioning

confidence: 99%

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A genetic algorithm for shortest path with real constraints in computer networks

AlGhamdi

Hamed²,

Alghamdi³

et al. 2023

IJECE

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<span lang="EN-US">The shortest path problem has many different versions. In this manuscript, we proposed a muti-constrained optimization method to find the shortest path in a computer network. In general, a genetic algorithm is one of the common heuristic algorithms. In this paper, we employed the genetic algorithm to find the solution of the shortest path multi-constrained problem. The proposed algorithm finds the best route for network packets with minimum total cost, delay, and hop count constrained with limited bandwidth. The new algorithm was implemented on four different capacity networks with random network parameters, the results showed that the shortest path under constraints can be found in a reasonable time. The experimental results showed that the algorithm always found the shortest path with minimal constraints.</span>

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Section: Resultssupporting

confidence: 59%

Section: Related Workmentioning

confidence: 99%

A genetic algorithm for shortest path with real constraints in computer networks

AlGhamdi

Hamed²,

Alghamdi³

et al. 2023

IJECE

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show abstract

“…We identified a diverse set of problems that belong to the class of constrained graph traversal problems. Although the shortest pathfinding problem is a well-known combinatorial optimization problem, its parameters are difficult to define exactly [1]. It is easy to see that the optimal route problem of a truck is practically a constrained shortest pathfinding problem [2], where the constraints describe the working hours limits of the driver and the availability of parking or the fuel capacity limits [3].…”

Section: Introductionmentioning

confidence: 99%

Generally Applicable Q-Table Compression Method and Its Application for Constrained Stochastic Graph Traversal Optimization Problems

Kegyes,

Kummer,

Süle

et al. 2024

Information

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We analyzed a special class of graph traversal problems, where the distances are stochastic, and the agent is restricted to take a limited range in one go. We showed that both constrained shortest Hamiltonian pathfinding problems and disassembly line balancing problems belong to the class of constrained shortest pathfinding problems, which can be represented as mixed-integer optimization problems. Reinforcement learning (RL) methods have proven their efficiency in multiple complex problems. However, researchers concluded that the learning time increases radically by growing the state- and action spaces. In continuous cases, approximation techniques are used, but these methods have several limitations in mixed-integer searching spaces. We present the Q-table compression method as a multistep method with dimension reduction, state fusion, and space compression techniques that project a mixed-integer optimization problem into a discrete one. The RL agent is then trained using an extended Q-value-based method to deliver a human-interpretable model for optimal action selection. Our approach was tested in selected constrained stochastic graph traversal use cases, and comparative results are shown to the simple grid-based discretization method.

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“…The SPP is the main combinatorial optimization problem in the graph theory environments, which can be promoted to FSs to handle ambiguity in the graphs, studied by [15][16][17]. The non-parametric DEA procedure is an appropriate tool in productivity measurement and evaluates the relative efficiency in the decision-making unit.…”

Section: Introductionmentioning

confidence: 99%

(α₁, α₂)-Cut Sets of Reliability Measures in Moore and Bilikam Lifetime Family Using the Generalized Intuitionistic Fuzzy Numbers

Zahra,

Ezzatallah,

Einolah

2023

IJFIS

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The parameters of lifetime distribution are frequently measured with some imprecision. However, classical lifetime analyses are based on precise measurement assumptions and cannot handle parameter imprecision. Accordingly, to accommodate the imprecision, the generalized intuitionistic fuzzy reliability analysis is preferred over classical reliability analysis. In reliability analysis, generalized intuitionistic fuzzy parameters provide a flexible model and elucidate the uncertainty and vagueness demanded in the reliability analysis. This study generalizes the parameters and reliability characteristics of the Moore and Bilikam family to cover the fuzziness of the lifetime parameters based on the generalized intuitionistic fuzzy numbers. The Moore and Bilikam family includes several lifetime distributions, such that the resulting reliability measures are more comprehensive than other lifetime distributions. The generalized intuitionistic fuzzy reliability functions and their α 1 -cut and α 2 -cut sets are provided, such as the reliability, conditional reliability, and hazard rate functions with generalized intuitionistic fuzzy parameters. We also evaluate the bands with upper and lower bounds in reliability measures than the curve. Based on a numerical example, the generalized intuitionistic fuzzy reliability measures are provided based on the Weibull distribution of the Moore and Bilikam family.

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An algorithmic approach for finding the fuzzy constrained shortest paths in a fuzzy graph

Cited by 10 publications

References 35 publications

A genetic algorithm for shortest path with real constraints in computer networks

A genetic algorithm for shortest path with real constraints in computer networks

Generally Applicable Q-Table Compression Method and Its Application for Constrained Stochastic Graph Traversal Optimization Problems

(α₁, α₂)-Cut Sets of Reliability Measures in Moore and Bilikam Lifetime Family Using the Generalized Intuitionistic Fuzzy Numbers

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