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By Catherine C. McGeoch

"Computational experiments on algorithms can complement theoretical research via displaying what algorithms, implementations, and speed-up tools paintings top for particular machines or difficulties. This booklet courses the reader throughout the nuts and bolts of the foremost experimental questions: What may still I degree? What inputs may still I try? How do I study the knowledge? Answering those questions wishes rules from set of rules design Read more...

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A newsworthy experiment produces outcomes that are interesting and useful to the research community, and therefore publishable. Two prerequisites for newsworthy experiments are wise choice of experimental subject (so that interesting results can reasonably be expected) and familiarity with the current literature (so that new results can be recognized). ” Tips for increasing generality, relevance, and credibility of experimental results are presented throughout this section. The rest of the section considers how to create experiments that meet these goals.

The permutations are selected so that the color count cannot increase at each iteration. This algorithm was one of several evaluated in the DIMACS Challenge on Graph Coloring [17]. The original C implementation may be downloaded from Joseph Culberson’s Web site [11]. 7, called SIG, may be downloaded from AlgLab. Here’s how it works: SIG starts by reading an input graph G and assigning it an initial coloring, according to a rule specified by the parameter INITIAL. At each iteration, SIG groups the vertices by color according to the current coloring, reorders groups by a vertex rule V , and then reorders colors according to a color rule C.

We can recognize three kinds of parameters in algorithmic experiments: • Algorithm parameters are associated with the algorithm or the test program. For example, Random takes parameter I , which specifies a number of iterations. assignColor(c,v) functions could be implemented in different ways: the source code found in each function is a categorical parameter. • Instance parameters refer to properties of input instances. For example, input size is nearly always of interest – in graph coloring, input size is described by two parameters n and m.

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