Hackl, R. and Morgenstern, Ingo (1997) Rapid Close-to-Optimum Optimization by Genetic Algorithms. International Journal of Modern Physics C (ijmpc) 8 (5), pp. 1103-1117.
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In this article we consider the optimization of np-complete problems with a genetic algorithm. For "real word" problems we regard it to be sufficient to get close to the optimal solution without any guarantee of ever hitting it. Our algorithm was tested on two problem classes: the traveling salesman problem and the product ordering problem; the first is a standard problem, the latter a problem we were confronted with in a practical application. For all investigated problem instances we found very good solutions (<0.2% above optimum) in each run and even the global optimum in some runs on a Pentium/100 MHz-PC. For one instance of the TSP problem we could verify that the time spent to find the optimum follows a logarithmic normal distribution.
|Institutions:||Physics > Institute of Theroretical Physics > Professor Morgenstern|
|Keywords:||Optimization; Genetic Algorithms; Traveling Salesman; NP-Complete Problems|
|Subjects:||500 Science > 530 Physics|
|Created at the University of Regensburg:||Unknown|
|Deposited On:||23 Aug 2010 13:55|
|Last Modified:||23 Aug 2010 13:55|
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