scholarly journals Optimum Allocation of Centers in Transportation Networks by Means of Fuzzy Graph Bases

2013 ◽  
Author(s):  
Leonid Bershtein ◽  
Alexandr Bozhenyuk ◽  
Igor Rozenberg
Keyword(s):  
Transportation Networks ◽  
Optimum Allocation ◽  
Fuzzy Graph

scholarly journals The Method of Allocation Centers in Second Kind Fuzzy Graphs With the Largest Vitality Degree

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Alexander Bozhenyuk, Stanislav Belyakov, Margarita Knyazeva
Keyword(s):  
Fuzzy Set ◽  
Optimal Allocation ◽  
Optimal Location ◽  
Optimum Allocation ◽  
Service Center ◽  
Fuzzy Graph ◽  
Reachability Matrix ◽  
Fuzzy Graphs ◽  
Optimal Service ◽  
Definition Of

The problem of optimal allocation of service centers is considered in this paper. It is supposed that the information received from GIS is presented like second kind fuzzy graphs. Method of optimal location as method of finding vitality fuzzy set of second kind fuzzy graph is suggested. Basis of this method is building procedure of reachability matrix of second kind fuzzy graph in terms of reachability matrix of first kind fuzzy graph. This method allows solving not only problem of finding of optimal service centers location but also finding of optimal location k-centers with the greatest degree and selecting of service center numbers. The algorithm of the definition of vitality fuzzy set for second kind fuzzy graphs is considered. The example of finding optimum allocation centers in second kind fuzzy graph is considered too.

Hybrid maize breeding with doubled haploids: Comparison between selection criteria

2006 ◽  
Vol 54 (3) ◽  
pp. 343-350 ◽  
Author(s):  
C. F. H. Longin ◽  
H. F. Utz ◽  
A. E. Melchinger ◽  
J.C. Reif
Keyword(s):  
Selection Criteria ◽  
Doubled Haploids ◽  
Optimum Allocation ◽  
Finite Sample ◽  
Sample Sizes ◽  
Maize Breeding ◽  
Selection Gain ◽  
Breeding Programmes ◽  
Hybrid Maize ◽  
Breeding Resources

The optimum allocation of breeding resources is crucial for the efficiency of breeding programmes. The objectives were to (i) compare selection gain ΔGk for finite and infinite sample sizes, (ii) compare ΔGk and the probability of identifying superior hybrids (Pk), and (iii) determine the optimum allocation of the number of hybrids and test locations in hybrid maize breeding using doubled haploids. Infinite compared to finite sample sizes led to almost identical optimum allocation of test resources, but to an inflation of ΔGk. This inflation decreased as the budget and the number of finally selected hybrids increased. A reasonable Pk was reached for hybrids belonging to the q = 1% best of the population. The optimum allocations for Pk(q) and ΔGkwere similar, indicating that Pk(q) is promising for optimizing breeding programmes.

Best Neighbor Heuristic Search for Finding Minimum Paths in Transportation Networks

1998 ◽  
Vol 1651 (1) ◽  
pp. 48-52 ◽  
Author(s):  
Jeffrey L. Adler
Keyword(s):  
Heuristic Search ◽  
Transportation Networks ◽  
Transportation Network ◽  
Search Problems ◽  
A Algorithm ◽  
Running Time ◽  
Search Effort ◽  
Wide Range ◽  
Path Search ◽  
Sparse Networks

For a wide range of transportation network path search problems, the A* heuristic significantly reduces both search effort and running time when compared to basic label-setting algorithms. The motivation for this research was to determine if additional savings could be attained by further experimenting with refinements to the A* approach. We propose a best neighbor heuristic improvement to the A* algorithm that yields additional benefits by significantly reducing the search effort on sparse networks. The level of reduction in running time improves as the average outdegree of the network decreases and the number of paths sought increases.

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