A genetic algorithm for public transport driver scheduling
Computers and Operations Research - Special issue on genetic algorithms
Solving transportation problems with nonlinear side constraints with tabu search
Computers and Operations Research
Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Practical Handbook of Genetic Algorithms
Practical Handbook of Genetic Algorithms
Tabu Search
The Holding Problem with Real-Time Information Available
Transportation Science
Optimizing the distribution of shopping centers with parallel genetic algorithm
Engineering Applications of Artificial Intelligence
A tabu search approach to an urban transport problem in northern Spain
Computers and Operations Research
A simple multi-objective optimization algorithm for the urban transit routing problem
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A metaheuristic approach to the urban transit routing problem
Journal of Heuristics
Genetic algorithms for a two-agent single-machine problem with release time
Applied Soft Computing
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In this paper, a model for optimizing bus route headway is presented in a given network configuration and demand matrix, which aims to find an acceptable balance between passenger costs and operator costs, namely the maximization of service quality and the minimization of operational costs. An integrated approach is also proposed in the paper to determine the relative weights between passenger costs and operator costs. A parallel genetic algorithm (PGA), in which a coarse-grained strategy and a local search algorithm based on Tabu search are applied to improve the performance of genetic algorithm, is developed to solve the headway optimization model. Data collected in Dalian City, China, is used to verify the feasibility of the model and the algorithm. Results show that the reasonable resource assessment can increase the benefits of transit system.