The current structure of transportation networks is the result of long-term and often random processes in the past, so it is almost certain that it is not optimal for current needs. An urgent task is therefore to develop a method that allows for finding an optimal network structure that meets both current and projected needs. Due to the lack of an analytical description and the complexity of the issue, the use of artificial intelligence methods seems appropriate.It is very likely that for almost every set of input data, there are several different solutions of similar quality, so a reliable method should allow for the simultaneous discovery of most of them. The paper proposes a variant of a genetic algorithm that naturally generates alternative transportation network structures.
SEARCHING FOR ALTERNATIVE TRANSPORTATION NETWORK STRUCTURES USING A GENETIC ALGORITHM
The current network structure is usually the result of historical and often random long adaptation processes and it is almost sure not optimal for present demands.
It is an urgent task to develop a method for searching the optimal transportation network structure, suitable for present and forecast demands. In the absence of analytical description and due to the complexity the usage of artificial inteligency methods seems to be the most appropriate. It is very likely, there are a few solutions of similar quality for almost each input data set. Therefore, the credible method should make possible a simultaneous obtainment most of them. In the paper the variant of genetic algorithm is presented, which in natural way generates alternative structures of a transportation network. (…)
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Source: Logistyka Magazine