engleski

Comparison of solution representations for scheduling in the unrelated machines environment

Most scheduling problems belong to the class of NP hard problems. Because of that reason, search based approaches are often used in order to find solutions for scheduling problems. In this paper we compare several search-based approaches for finding solutions for the unrelated machines scheduling problem. These search based approaches use two different solution representations for the aforementioned problem and the representations are compared with each other. The first representation uses a permutation vector to encode the solution, while the second one uses a vector of floating point numbers. The results of the search based approaches are compared to several existing heuristics developed especially for solving the unrelated machines scheduling problem. We also perform a complexity analysis of the search- based approaches, in which we compute the time needed for them to outperform the problem specific heuristics.

Genetic algorithms; Dynamic scheduling

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