Comparison of Selected Algorithms Solving Vehicle Routing Problem with Simultaneous Delivery and Pickup
Ładowanie...
Data
2021
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
The Vehicle Routing Problem is a widely known combinatorial
optimization problem. A particular variant of this problem
is Vehicle Routing Problem with Simultaneous Delivery and Pickup
(VRPSDP). In this paper, two metaheuristics are compared in the
context of solving the VRPSDP - the Genetic Algorithm (GA) and
Ant Colony Optimization (ACO). Both implemented algorithms are
hybridized using local search operators. Implemented algorithms are
tested using well known Dethloff dataset. The final results show that,
in general, ACO gives more accurate results than GA, but it is worse
in terms of performance. The main reason for that is the difficulty of
incorporating local search operators into the Genetic Algorithm.
Opis
Słowa kluczowe
Vehicle Routing Problem, Vehicle Routing Problem with simultaneous delivery and pickup, genetic algorithm, ant colony optimization, problem z trasą pojazdu, problem z trasą pojazdu z jednoczesną dostawą i odbiorem, algorytm genetyczny, algorytm mrówkowy
Cytowanie
Michalik M., Ochelska-Mierzejewska J., Comparison of Selected Algorithms Solving Vehicle Routing Problem with Simultaneous Delivery and Pickup. W: TEWI 2021 (Technology, Education, Knowledge, Innovation), Wojciechowski A. (Ed.), Napieralski P. (Ed.), Lipiński P. (Ed.)., Seria: Monografie PŁ;Nr 2378, Wydawnictwo Politechniki Łódzkiej, Łódź 2021, s. 113-137, ISBN 978-83-66741-10-2, DOI 10.34658/9788366741102.9.