A combinatorial optimization approach for multi-label associative classification

2021 ◽  
pp. 108088
Author(s):  
Yuchun Zou ◽  
Chun-An Chou
Keyword(s):  
Combinatorial Optimization ◽  
Optimization Approach ◽  
Associative Classification

scholarly journals A Multi-Agent Proposal for the Resolution of BIBD instances

2016 ◽  
Vol 39 (2) ◽  
pp. 267 ◽  
Author(s):  
David Rodriguez ◽  
Enrique Darghan ◽  
Julio Monroy
Keyword(s):  
Combinatorial Optimization ◽  
Experimental Design ◽  
Tabu Search ◽  
Local Search ◽  
Current Literature ◽  
Hill Climbing ◽  
Optimization Approach ◽  
Search Spaces ◽  
Multi Agent ◽  
Multi Agents

<p>The problem with designing balanced incomplete blocks (BIBD) is enclosed within the combinatorial optimization approach that has been extensively used in experimental design. The present proposal addresses thi problem by using local search techniques known as Hill Climbing, Tabu Search, and an approach based considerable sized the use of Multi-Agents, which allows the exploration of diverse areas of search spaces. Furthermore, the use of a vector vision for the consideration associated with vicinity is presented. The experimental results prove the advantage of this technique compared to other proposals that are reported in the current literature.</p>

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