Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Combining different prioritization methods in the analytic hierarchy process synthesis
Computers and Operations Research
Artificial Intelligence
SEPADS'11 Proceedings of the 10th WSEAS international conference on Software engineering, parallel and distributed systems
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Making decision is the critical part in choosing the best solution. The decision maker can use Analytic Hierarchy Process (AHP) as a method in making decision. However, this method has been criticized mainly in priority derivation procedure. To solve this criticized; this paper proposes AHPEC which is using Evolutionary Computing (EC) to derive priorities in AHP. The AHPEC gives better result compare to the other prioritization methods based on accuracy of derived priorities.