TY - GEN

T1 - Swarm Intelligence Technique for Capacity Optimization of a Transportation Network

AU - Крылатов, Александр Юрьевич

AU - Кузнецова, Дарья Сергеевна

PY - 2024

Y1 - 2024

N2 - Today artificial intelligence systems support efficient management in different fields of social activities. In particular, congestion control in modern networks seems to be impossible without proper mathematical models of traffic flow assignment. Thus, the network design problem can be referred to as Stackelberg game with independent lower-level drivers acting in a non-cooperative manner to minimize individual costs. In turn, upper-level decision-maker seeks to minimize overall travel time in the network by investing in its capacity. Hence, the decision-maker faces the challenge with a hierarchical structure which solution important due to its influence on the sustainable development of modern large cities. However, well-known that a bilevel programming problem is often strongly NP-hard, while the hierarchical optimization structure of a bilevel problem raises such difficulties as non-convexity and disconnectedness. The present paper is devoted to the swarm intelligence technique for capacity optimization of a transportation network. To this end, we develop the bilevel evolutionary algorithm based on swarm intelligence to cope with the continuous transportation network design problem. The findings of the paper give fresh insights to transport engineers and algorithm developers dealing with network design.

AB - Today artificial intelligence systems support efficient management in different fields of social activities. In particular, congestion control in modern networks seems to be impossible without proper mathematical models of traffic flow assignment. Thus, the network design problem can be referred to as Stackelberg game with independent lower-level drivers acting in a non-cooperative manner to minimize individual costs. In turn, upper-level decision-maker seeks to minimize overall travel time in the network by investing in its capacity. Hence, the decision-maker faces the challenge with a hierarchical structure which solution important due to its influence on the sustainable development of modern large cities. However, well-known that a bilevel programming problem is often strongly NP-hard, while the hierarchical optimization structure of a bilevel problem raises such difficulties as non-convexity and disconnectedness. The present paper is devoted to the swarm intelligence technique for capacity optimization of a transportation network. To this end, we develop the bilevel evolutionary algorithm based on swarm intelligence to cope with the continuous transportation network design problem. The findings of the paper give fresh insights to transport engineers and algorithm developers dealing with network design.

KW - Bilevel optimization

KW - Network design problem

KW - PSO algorithm

UR - https://www.mendeley.com/catalogue/c98500d5-b195-3ef7-8597-d1ede2dbcde9/

U2 - 10.1007/978-3-031-48751-4_15

DO - 10.1007/978-3-031-48751-4_15

M3 - статья в сборнике материалов конференции

SN - 9783031487507

T3 - Communications in Computer and Information Science

SP - 202

EP - 213

BT - Advances in Optimization and Applications

PB - Springer Nature

Y2 - 18 September 2023 through 22 September 2023

ER -