By Hans-Paul Schwefel
Hans-Paul Schwefel explains and demonstrates numerical optimization tools and algorithms as utilized to computing device calculations--which should be rather valuable for hugely parallel pcs. The disk comprises all algorithms provided within the ebook.
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Example text
Step 2: (Line search) By varying xi within the interval a(ik) b(ik)] search for the relative minimum x0 with the required accuracy " (line search with an interval division procedure or an iterative interpolation method): (k i;1) + s e )g F (x0) = min i s fF (x Step 3: (Check for improvement) If F (x0) F (x(k i;1)), then set x(k i) = x0 otherwise set x(k i) = x(k i;1). Step 4: (Inner loop over all coordinates) If i < n, increase i i + 1 and go to step 1. Step 5: (Termination criterion, outer iteration loop) 0) = x(k n) .
0:25. If the above rules for increasing and reducing the step lengths are combined, a very exible procedure is obtained. Dixon (1972a) calls it the success/failure routine. If a starting interval a(0) b(0)] is already at hand, however, there are signi cantly better strategies for successively reducing the size of the interval. 2 Interval Division Methods If an equidistant division method is applied repeatedly, the interval of uncertainty is reduced at each step by the same factor , and thus for k steps by k .
2 Sequential Methods If the trials for determining a minimum can be made sequentially, the intermediate results retained at a given time can be used to locate the next trial of the sequence more favorably than would be possible without this information. With the digital computers usually available nowadays, which work in a serial way, one is actually obliged to execute all steps one after the other. Sequential methods, in which the solution is approached in a stepwise, or iterative, manner, are advantageous here.