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Sample text

The experiments made indicate that parallel computing can be beneficial when solving real-time DARP. Except for tabu search, also other metaheuristics have been tried on the DARP. Baugh et al. (1998) use simulated annealing to solve the DARP. A cluster-first, route-second approach is used. Simulated annealing is used for the clustering, and a greedy algorithm is used for the routing after that the clusters are made. The clustering starts with randomly assigning customers to clusters. Two types of operations are then used to alter the clusters.

Diana & Dessouky (2004) presented a parallel regret insertion heuristic to solve large instances of the DARP. Data sets of 500 and 1000 requests have been tested. Toth & Vigo (1997) developed a parallel insertion heuristic to be able to find good solutions also to large instances within quite small computational times. More special instances of the dial-a-ride problem have also been studied. In Daganzo (1978) an analytic model is presented, that forecast average waiting times and ride times for a dial-a-ride service.

Also in Martins & Pato (1998) a combination of train and bus services is studied. The problem is to design a feeder bus network given a rail network, with the objective to minimize a cost function considering both the operator’s and the customers’ interests. 4 that combines features of both fixed route and dial-a-ride services are of course interesting. However, since a fixed route service always will be necessary to provide a service effective enough for those who demand a fast public transportation service, a combination of a fixed route service and a demand responsive service seems more useful.

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