TY - CHAP
T1 - The railway network design, line planning and capacity problem
T2 - An adaptive large neighborhood search metaheuristic
AU - Canca, David
AU - De-Los-Santos, Alicia
AU - Laporte, Gilbert
AU - Mesa, Juan A.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - In this chapter, we propose a model for the Railway Network Design and Line Planning (RNDLP) problem, integrating the two classical first stages in the Railway Planning Process. The network design problem incorporates costs relative to the network construction, proposing a set of candidate lines. The line planning problem is in charge of determining optimal frequencies and consequently train operations, taking into account rolling stock, personnel and fleet acquisition costs. Both problems are intertwined because the line design influences the selection of frequencies and the corresponding fleet size. We consider the existence of an alternative transportation mode for each origin-destination pair in the network. In this way, the rapid railway mode competes against the alternative mode for a given certain demand, represented by a global origin-destination matrix. Passengers choose their transportation mode according to their own utility. Since the problem is computationally intractable for realistic size scenarios, we develop an Adaptive Large Neighborhood Search (ALNS) algorithm, which can handle the RNDLP problem. As illustration, the ALNS performance is demonstrated in an artificial instance using estimated data from literature.
AB - In this chapter, we propose a model for the Railway Network Design and Line Planning (RNDLP) problem, integrating the two classical first stages in the Railway Planning Process. The network design problem incorporates costs relative to the network construction, proposing a set of candidate lines. The line planning problem is in charge of determining optimal frequencies and consequently train operations, taking into account rolling stock, personnel and fleet acquisition costs. Both problems are intertwined because the line design influences the selection of frequencies and the corresponding fleet size. We consider the existence of an alternative transportation mode for each origin-destination pair in the network. In this way, the rapid railway mode competes against the alternative mode for a given certain demand, represented by a global origin-destination matrix. Passengers choose their transportation mode according to their own utility. Since the problem is computationally intractable for realistic size scenarios, we develop an Adaptive Large Neighborhood Search (ALNS) algorithm, which can handle the RNDLP problem. As illustration, the ALNS performance is demonstrated in an artificial instance using estimated data from literature.
KW - Adaptive large neighborhood search
KW - Line planning
KW - Network design
KW - Railway rapid transit
UR - http://www.scopus.com/inward/record.url?scp=85022179058&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-57105-8_9
DO - 10.1007/978-3-319-57105-8_9
M3 - Chapter or section
AN - SCOPUS:85022179058
SN - 9783319571041
T3 - Advances in Intelligent Systems and Computing
SP - 198
EP - 219
BT - Advances in Intelligent Systems and Computing
A2 - Zak, J.
A2 - Hadas, Y.
A2 - Rossi, R.
PB - Springer Verlag
CY - Cham, Switzerland
ER -