Keyphrases
Multi-objective Approach
100%
Variable Demand
100%
Transport Equity
100%
Transit Network Design Problem
100%
Transit Network
75%
Service Level
50%
Urban Environment
25%
South Korea
25%
Network Design
25%
Logit
25%
Mode Choice
25%
System Efficiency
25%
Solution Set
25%
Local Search Algorithm
25%
Non-dominated Sorting Genetic Algorithm (NSGA-II)
25%
Transit Demand
25%
Overlapping Distribution
25%
Transit Service
25%
User Inconvenience
25%
Private Car
25%
Transit Operator
25%
Vehicle Traffic Volume
25%
Key Influencing Factors
25%
Computer Science
Multiobjective
100%
Network Design Problem
100%
Genetic Algorithm
33%
Network Design
33%
Objective Function
33%
Urban Environment
33%
System Efficiency
33%
Local Search Method
33%
Influential Factor
33%
Private Vehicle
33%
Social Sciences
Variance
100%
South Korea
50%
Urban Environment
50%
Genetic Algorithm
50%
Traffic Volume
50%
Mode Choice
50%