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Salih O. Duffuaa

dblp:94/4711 · DBLP profile ↗
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4ranked-venue papers
1as first author
2since 2021 · last 2023
0000-0001-6128-9184ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4 · 1 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Graph algorithms and graph theory · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Graph algorithms and graph theory
graph matching		 0.011993
A Linear Programming Approach for the Weighted Graph Matching Problem · IEEE Trans. Pattern Anal. Mach. Intell. 1993
Graph algorithms and graph theory › graph matching
weighted graph matching		 0.011993
A Linear Programming Approach for the Weighted Graph Matching Problem · IEEE Trans. Pattern Anal. Mach. Intell. 1993

Methods — techniques the papers use, named apart from their topics

simplex algorithm · 0.0linear programming · 0.0hungarian method · 0.0
YearPublicationVenuePosition
2023 Performance evaluation of meta-heuristic algorithms for designing multi-objective multi-product multi-echelon supply chain network
Salih O. Duffuaa, Awsan Mohammed
 Soft Comput.1
2022 A hybrid algorithm based on tabu search and generalized network algorithm for designing multi-objective supply chain networks
Awsan Mohammed, Salih O. Duffuaa
 Neural Comput. Appl.2
2020 A tabu search based algorithm for the optimal design of multi-objective multi-product supply chain networks
Awsan Mohammed, Salih O. Duffuaa
 Expert Syst. Appl.2
1993 A Linear Programming Approach for the Weighted Graph Matching Problem
abstract
A linear programming (LP) approach is proposed for the weighted graph matching problem. A linear program is obtained by formulating the graph matching problem in L/sub 1/ norm and then transforming the resulting quadratic optimization problem to a linear one. The linear program is solved using a simplex-based algorithm. Then, approximate 0-1 integer solutions are obtained by applying the Hungarian method on the real solutions of the linear program. The complexity of the proposed algorithm is polynomial time, and it is O(n/sup 6/L) for matching graphs of size n. The developed algorithm is compared to two other algorithms. One is based on an eigendecomposition approach and the other on a symmetric polynomial transform. Experimental results showed that the LP approach is superior in matching graphs than both other methods.>
H. A. Almohamad, Salih O. Duffuaa
 IEEE Trans. Pattern Anal. Mach. Intell.2