TY - JOUR
T1 - Time-dependent rural postman problem
T2 - time-space network formulation and genetic algorithm
AU - Xin, Jianbin
AU - Yu, Benyang
AU - D’Ariano, Andrea
AU - Wang, Heshan
AU - Wang, Meng
PY - 2021
Y1 - 2021
N2 - In this paper, a new time-space network model is proposed for addressing the time-dependent rural postman problem (TDRPP) of a single vehicle. The proposed model follows the idea of arc-path alternation to form a feasible and complete route. Based on the proposed model, the time dependency of the TDRPP is better described to capture its dynamic process, compared to the existing methods using a piecewise constant function with limited intervals. Furthermore, the property of first-in-first-out (FIFO) can be satisfied with the time spent on each arc. We investigate the FIFO property for the considered time-dependent network and key optimality property for the TDRPP. Based on this property, a dedicated genetic algorithm (GA) is proposed to efficiently solve the considered TDRPP that suffers from computational intractability for large-scale cases. Comprehensive simulation experiments are conducted for various time-dependent networks to show the effectiveness of the proposed GA.
AB - In this paper, a new time-space network model is proposed for addressing the time-dependent rural postman problem (TDRPP) of a single vehicle. The proposed model follows the idea of arc-path alternation to form a feasible and complete route. Based on the proposed model, the time dependency of the TDRPP is better described to capture its dynamic process, compared to the existing methods using a piecewise constant function with limited intervals. Furthermore, the property of first-in-first-out (FIFO) can be satisfied with the time spent on each arc. We investigate the FIFO property for the considered time-dependent network and key optimality property for the TDRPP. Based on this property, a dedicated genetic algorithm (GA) is proposed to efficiently solve the considered TDRPP that suffers from computational intractability for large-scale cases. Comprehensive simulation experiments are conducted for various time-dependent networks to show the effectiveness of the proposed GA.
KW - Genetic algorithm
KW - Rural postman problem
KW - Time-dependent network
KW - Time-space network model
UR - http://www.scopus.com/inward/record.url?scp=85105369496&partnerID=8YFLogxK
U2 - 10.1007/s12351-021-00639-0
DO - 10.1007/s12351-021-00639-0
M3 - Article
AN - SCOPUS:85105369496
VL - 22
SP - 2943
EP - 2972
JO - Operational Research
JF - Operational Research
SN - 1109-2858
IS - 3
ER -