Jens Arndt

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This paper uses an entertaining student "sports" game to illustrate that GAs can be adapted to problems with uncertain properties and complexity. These problems can be solved easily through GAs within a few seconds. Contrary to this, using standard MILP techniques does not yield results in a reasonable time.
The IS development industry is currently undergoing profound changes. The well established, large system developers (hubs) take the lead in establishing partner networks with much smaller, often young companies (spokes). This paper takes the perspective of these spokes and seeks to understand their motivations for entering into such partner networks.(More)
— Important advantage of genetic algorithms (GAs) are their ease of use, their wide applicability, and their good performance for a wide range of different problems. GAs are able to find good solutions for many problems even if the problem is complicated and its properties are not well known. In contrast, classical optimization approaches like linear(More)
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