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We propose particle swarm optimization (PSO) algorithm for solving transport continuous network design problems (CNDP), and give sensitivity analysis for the parameters used in PSO. The CNDP is formulated as a bi-level programming model. The sensitivity analysis method, one-at-a-time designs (OATD), is used to analyze the effects of parameters. Numerical example demonstrates that PSO is an effective...
In this paper, parameters choices of simulated annealing for continuous network design problems are discussed. A bi-level programming model for continuous network design problem is introduced. Objective function of the upper level is defined as the sum of the total travel time on the network and the total investment costs of link capacity expansions. The lower level problem is the user equilibrium...
This paper is focus on the parameters settings using genetic algorithm to solve continuous network design problems (CNDP). The CNDP is formulated as a bi-level programming model. The sensitive analyses method, one-at-a-time designs, is used to analyze the effects of parameters. The analyses demonstrated that the setting of population size has clear effects to the solution; the effects of crossover...
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