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Abstract:

This paper gives an introduction into evolutionary computation, in particular in the light of multiobjective optimization, and demonstrates how evolutionary algorithms can be used to tackle a highly demanding application in telecommunications, namely the design of a network processor. 1 Introductory Example To illustrate the basic principles of multiobjective optimization and evolutionary algorithms, consider the following example: given is a set of items together with a profit and a weight associated with each item; the goal is to determine a subset of items such that the overall profit, i.e., the sum of the profits of the selected items, is maximum, while the overall weight, i.e., the sum of the weights of the selected items, is minimal. This problem is generally denoted as knapsack problem. Now assume that four items are available: a camera (weight = 750, profit=5), a thermos flask (weight = 1500, profit=8), a pocket knife (weight = 300, profit=7), and a book (weight = 1000, profit=3). The set of all possible selections contains 16

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