Title :
A new evolutionary programming approach based on simulated annealing with local cooling schedule
Author :
Cho, Hyeon-Joong ; Oh, Se-young ; Choi, Doo-Hyun
Author_Institution :
Dept. of Electr. Eng., Pohang Univ. of Sci. & Technol., South Korea
Abstract :
The NPOSA (New Population-Oriented Simulated Annealing) technique is introduced as an efficient global search tool to solve optimization problems. Unlike the conventional simulated annealing or its hybrid algorithms, each individual in the population can intelligently plan its own annealing schedule in an adaptive fashion to the given problem at hand. This not only enhances the search speed but furthermore yields a solution near the global optimum. This technique has been applied to solve the traveling salesman problem (TSP) for combinatorial optimization, as well as a continuous function optimization problem, to demonstrate its validity and effectiveness
Keywords :
functional analysis; genetic algorithms; planning (artificial intelligence); programming; scheduling; search problems; simulated annealing; travelling salesman problems; NPOSA; adaptive planning; combinatorial optimization; continuous function optimization; evolutionary programming; global optimum; global search tool; intelligent annealing schedule planning; local cooling schedule; population-oriented simulated annealing; search speed; traveling salesman problem; Adaptive scheduling; Costs; Electronic mail; Electronics cooling; Genetic programming; Scheduling algorithm; Simulated annealing; Solids; Temperature distribution; Traveling salesman problems;
Conference_Titel :
Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4869-9
DOI :
10.1109/ICEC.1998.700096