scholarly journals Optimal components assignment problem for a flow network with node failure using fuzzy optimization

2021 ◽  
pp. 101601
Author(s):  
M.R. Hassan ◽  
H. Hamdy ◽  
Salem Alkhalaf ◽  
Ayman M Bahaa Eldin ◽  
Mahrous Ahmed ◽  
...  
Keyword(s):  
Assignment Problem ◽  
Fuzzy Optimization ◽  
Node Failure ◽  
Flow Network

scholarly journals Mathematical approaches for improving the efficiency of railway transport

2020 ◽  
Vol 10 (1) ◽  
pp. 57-63
Author(s):  
Martin Vojtek ◽  
Martin Kendra ◽  
Vladislav Zitrický ◽  
Jaromír Široký
Keyword(s):  
Assignment Problem ◽  
Operational Research ◽  
Applied Mathematics ◽  
Optimal Solution ◽  
Operating Costs ◽  
Railway Transport ◽  
Flow Network ◽  
Railway Vehicles ◽  
Mathematical Algorithms ◽  
Entrepreneurial Activities

AbstractCurrent business trends push transport companies to improve the efficiency of their entrepreneurial activities, what is closely related to costs reduction and revenues increase. Many transport companies achieve it empirically, but some mathematical algorithms, mainly from operational research, can be used to improve the efficiency of railway transport by finding the optimal solution of specific problems. The paper is focused on using of selected methods from applied mathematics in railway transport. These methods are used mainly for improving the operational efficiency of the transport company, what tends to decrease overall operating costs. Major impact is done by efficient use of railway vehicles and train staff. It can be achieved by optimization as a flow network problem or assignment problem, what is further described in the paper. Mathematical approaches can also positively influence the whole logistic process.

Persistence of Hybrid Diagnosability of Regular Networks Under Testing Diagnostic Model

2020 ◽  
Author(s):  
Guanqin Lian ◽  
Shuming Zhou ◽  
Eddie Cheng ◽  
Jiafei Liu ◽  
Gaolin Chen
Keyword(s):  
Fault Tolerance ◽  
Assignment Problem ◽  
Diagnostic Model ◽  
Multiprocessor Systems ◽  
Node Failure ◽  
Pmc Model ◽  
Free Network ◽  
Delta G ◽  
Regular Networks ◽  
Fault Diagnosability

Abstract Diagnosability is an important metric to fault tolerance and reliability for multiprocessor systems. However, plenty of research on fault diagnosability focuses on node failure. In practical scenario, not only node failures take place but also link malfunctions may arise. In this work, we investigate the diagnosability of general regular networks with failing nodes as well as missing malfunctional links. Let $S$ be a set of the missing links and broken-down nodes. We first prove that the diagnosability of the survival graph $G\setminus S$ persists $\delta (G\setminus S)$ under the PMC model (Preparata, F.P., Metze, G. and Chien, R.T. (1967) On the connection assignment problem of diagnosable systems. IEEE Trans. Electron. Comput., EC-16, 848–854) for a $t$-regular and $t$-connected triangle-free network $G$ subject to $|S|\leq t-1$ and $|V(G)|\geq 3t-2$ ($t\geq 3$). Furthermore, we determine the diagnosability of $G\setminus S$ for some kinds of extensively explored $t$-regular networks with triangles subject to $|S|\leq t-1$ ($t\geq 3$).

scholarly journals A genetic algorithm to solve the robust design problem for a Flow Network with Node Failure

2020 ◽  
Vol 8 (4) ◽  
pp. 01-10
Author(s):  
Noha Hamdy ◽  
Moatamad Refaat Hassan ◽  
Mohamed Eid Hussein
Keyword(s):  
Genetic Algorithm ◽  
Robust Design ◽  
Design Problem ◽  
Network Reliability ◽  
Approximate Algorithm ◽  
Node Failure ◽  
Flow Network ◽  
Optimal Capacity ◽  
Optimal Node ◽  
Node Capacity

The robust design problem in a flow network is defined as search optimal node capacity that can be assigned such that the network still survived even under the node’s failure. This problem is considered as an NP-hard. So, this paper proposes a genetic algorithm-based approach to solve it for a flow network with node failure. The proposed based genetic approach is used to assign the optimal capacity for each node to minimize the total capacities and maximize the network reliability. The proposed approach takes the capacity for each critical node should have the maximum capacity (usually equals to the demand value) to alleviate that the reliability to drop to zero. Three network examples are used to show the efficiency of our algorithm. Also, the results obtained by our approach are compared with those obtained by the previous approximate algorithm.

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