TY - JOUR
T1 - A Comparative Study of Three Evolutionary Algorithms Incorporating Different Amounts of Domain Knowledge for Node Covering Problem
AU - He, Jun
AU - Yao, Xin
AU - Li, Jin
PY - 2005/5/1
Y1 - 2005/5/1
N2 - This paper compares three different evolutionary algorithms for solving the node covering problem: EA-I relies on the definition of the problem only without using any domain knowledge, while EA-II and EA-III employ extra heuristic knowledge. In theory, it is proven that all three algorithms can find an optimal solution in finite generations and find a feasible solution efficiently; but none of them can find the optimal solution efficiently for all instances of the problem. Through experiments, it is observed that all three algorithms can find a feasible solution efficiently, and the algorithms with extra heuristic knowledge can find better approximation solutions, but none of them can find the optimal solution to the first instance efficiently. This paper shows that heuristic knowledge is helpful for evolutionary algorithms to find good approximation solutions, but it contributes little to search for the optimal solution in some instances.
AB - This paper compares three different evolutionary algorithms for solving the node covering problem: EA-I relies on the definition of the problem only without using any domain knowledge, while EA-II and EA-III employ extra heuristic knowledge. In theory, it is proven that all three algorithms can find an optimal solution in finite generations and find a feasible solution efficiently; but none of them can find the optimal solution efficiently for all instances of the problem. Through experiments, it is observed that all three algorithms can find a feasible solution efficiently, and the algorithms with extra heuristic knowledge can find better approximation solutions, but none of them can find the optimal solution to the first instance efficiently. This paper shows that heuristic knowledge is helpful for evolutionary algorithms to find good approximation solutions, but it contributes little to search for the optimal solution in some instances.
KW - performance analysis
KW - optimization methods
KW - algorithm design
KW - heuristic knowledge
UR - http://www.scopus.com/inward/record.url?scp=18544379627&partnerID=8YFLogxK
U2 - 10.1109/TSMCC.2004.841903
DO - 10.1109/TSMCC.2004.841903
M3 - Article
VL - 35
SP - 266
EP - 271
JO - IEEE Transactions on Systems, Man and Cybernetics, Part C
JF - IEEE Transactions on Systems, Man and Cybernetics, Part C
IS - 2
ER -