This paper proposes new algorithms for the Binate Covering Problem (BCP), a well-known restriction of Boolean Optimization. Binate Covering finds application in many areas of Comp...
We present an evolutionary methodology that explores the evolution of network topology when a uniform growth of the network traffic is considered. The network redesign problem is ...
Abstract--This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA i...
The decision tree is one of the most fundamental ing abstractions. A commonly used type of decision tree is the alphabetic binary tree, which uses (without loss of generality) &quo...
This paper deals with fair assignment problems in decision contexts involving multiple agents. In such problems, each agent has its own evaluation of costs and we want to find a f...