logit models are one of the most important discrete choice models and they play an important role in describing decision makers’ choices among alternatives. in this paper the multi-nominal logit models has been used in mode choice modeling of isfahan. despite the availability of different mathematical computer programs there are not so many programs available for estimating discrete choice mode...

TThe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. This paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. As a novelty, the proposed controller employs a simple Gaussian Radial-Basis-Function Network as an uncertainty estimator. The proposed netw...

Robust topology optimization has gained importance during the last years. This paper presents a robust approach to topology optimization using multiobjective evolutionary algorithms. A key contribution of our approach is that our optimization model handles structural robustness through the first two objectives, namely, the expected compliance and its variance; whereas a third objective incorpor...

This report documents the development of several transportation optimization models under uncertainty. First, a robust evacuation transportation planning model for freeway traffic systems was developed, in which demand is uncertain. The study results provide preliminary evidence that routing traffic using such a robust, optimization-based model can improve the average objective performance. Nex...

This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances and discretization error. Parameters of the fuzzy estimator are adapted to minimize the estimat...