By Carl Henrik Hall.
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Extra resources for A framework for evaluation and design of an integrated public transport system
3 A Framework for Planning of Integrated Services Many of the problems involved in planning of a public transport system are complex, and therefore it is difficult to find good solutions to them (as previously described in Chapter 2). In addition, there is also the problem of how the solution of one problem affects the solutions of other problems. Even if optimal solutions are not required to all problems (or even to any of the problems) it is many times hard to know how the different problems affect each other.
2002) use genetic algorithms to solve the DARP. Pick-up and drop-off nodes are stringed out by random and in this way creating the individuals of the first population. After this, the algorithm iterates for 1000 generations, where for each iteration the individuals with the best fitness value are kept as the next population. The experiments made focuses on comparison of the genetic algorithm, a standard edge exchange algorithm (2-opt algorithm) and a combination of the genetic algorithm and the 2-opt.
In this way all computation is done in either the GIS or in the modeling tool. As an example, input data can be prepared in the GIS, exported to the external modeling tool and computed there, and thereafter exported back to GIS for visualization or further analyzes of the results. This can either be done manually, or called from the GIS interface. If done manually, the new functionality of the modeling tool is actually never added to the GIS. The second way is to add macros written inside the GIS, using languages provided by the GIS.
A framework for evaluation and design of an integrated public transport system by Carl Henrik Hall.