Simultaneous perturbation stochastic approximation algorithm for solving stochastic problems of transportation network analysis: performance evaluation
EE Ozguven, K Ozbay - Transportation research record, 2008 - journals.sagepub.com
Stochastic optimization has become one of the important modeling approaches in
transportation network analysis. For example, for traffic assignment problems based on
stochastic simulation, it is necessary to use a mathematical algorithm that iteratively seeks
out the optimal, the suboptimal solution, or both, because an analytical (closed-form)
objective function is not available. Therefore, efficient stochastic approximation algorithms
that can find optimal or suboptimal solutions to these problems are needed. The method of …
transportation network analysis. For example, for traffic assignment problems based on
stochastic simulation, it is necessary to use a mathematical algorithm that iteratively seeks
out the optimal, the suboptimal solution, or both, because an analytical (closed-form)
objective function is not available. Therefore, efficient stochastic approximation algorithms
that can find optimal or suboptimal solutions to these problems are needed. The method of …
[PDF][PDF] Performance evaluation of simultaneous perturbation stochastic approximation algorithm for solving stochastic transportation network analysis problems
EE Ozguven, K Ozbay - Proceedings of the 87th Annual Meeting on …, 2008 - jhuapl.edu
Stochastic optimization has become one of the important modeling approaches in the
transportation network analysis. For example, for traffic assignment problems based on
stochastic simulation, it is necessary to use a mathematical algorithm that iteratively seeks
out the optimal and/or suboptimal solution because an analytical (closed-form) objective
function is not available. Therefore, there is a need for efficient stochastic approximation
algorithms that can find optimal and/or suboptimal solutions to these problems. Method of …
transportation network analysis. For example, for traffic assignment problems based on
stochastic simulation, it is necessary to use a mathematical algorithm that iteratively seeks
out the optimal and/or suboptimal solution because an analytical (closed-form) objective
function is not available. Therefore, there is a need for efficient stochastic approximation
algorithms that can find optimal and/or suboptimal solutions to these problems. Method of …