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A Two-stage Model for a Day-ahead Paratransit Planning Problem
Electronic Notes in Discrete Mathematics 25 (2006) 35 www.elsevier.com/locate/endm
A Two-stage Model for a Day-ahead Paratransit Planning Problem M.L.A.G. Cremers, 1 W.K. Klein Haneveld, and M.H. van der Vlerk Faculty of Economics University of Groningen P.O. Box 800, 9700 AV Groningen, the Netherlands
Abstract We consider a dynamic planning problem for the transport of elderly and disabled people. In particular, we focus on a decision to take one day ahead: which requests should be served with own vehicles, and which requests should be subcontracted to taxis? We call this problem the Day-ahead Paratransit Planning problem (DaPP). The model developed for DaPP is a non-standard two-stage integer recourse model from stochastic programming. Both stages consist of two parts: requests are first clustered into routes, and these routes are in turn assigned to vehicles (own vehicles and taxis). To solve this model, a genetic algorithm approach is used. Computational results are presented for randomly generated data sets. Keywords: Paratransit Transport, Stochastic Programming, Genetic Algorithms
1
Email: [email protected]
1571-0653/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.endm.2006.06.059
A Two-stage Model for a Day-ahead Paratransit Planning Problem M.L.A.G. Cremers, 1 W.K. Klein Haneveld, and M.H. van der Vlerk Faculty of Economics University of Groningen P.O. Box 800, 9700 AV Groningen, the Netherlands
Abstract We consider a dynamic planning problem for the transport of elderly and disabled people. In particular, we focus on a decision to take one day ahead: which requests should be served with own vehicles, and which requests should be subcontracted to taxis? We call this problem the Day-ahead Paratransit Planning problem (DaPP). The model developed for DaPP is a non-standard two-stage integer recourse model from stochastic programming. Both stages consist of two parts: requests are first clustered into routes, and these routes are in turn assigned to vehicles (own vehicles and taxis). To solve this model, a genetic algorithm approach is used. Computational results are presented for randomly generated data sets. Keywords: Paratransit Transport, Stochastic Programming, Genetic Algorithms
1
Email: [email protected]
1571-0653/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.endm.2006.06.059