@article{(Open Science Index):https://publications.waset.org/pdf/11401,
	  title     = {Equivalence Class Subset Algorithm},
	  author    = {Jeffrey L. Duffany},
	  country	= {},
	  institution	= {},
	  abstract     = {The equivalence class subset algorithm is a powerful
tool for solving a wide variety of constraint satisfaction problems and
is based on the use of a decision function which has a very high but
not perfect accuracy. Perfect accuracy is not required in the decision
function as even a suboptimal solution contains valuable information
that can be used to help find an optimal solution. In the hardest
problems, the decision function can break down leading to a
suboptimal solution where there are more equivalence classes than
are necessary and which can be viewed as a mixture of good decision
and bad decisions. By choosing a subset of the decisions made in
reaching a suboptimal solution an iterative technique can lead to an
optimal solution, using series of steadily improved suboptimal
solutions. The goal is to reach an optimal solution as quickly as
possible. Various techniques for choosing the decision subset are
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {3},
	  number    = {5},
	  year      = {2009},
	  pages     = {1309 - 1314},
	  ee        = {https://publications.waset.org/pdf/11401},
	  url   	= {https://publications.waset.org/vol/29},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 29, 2009},