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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 models. Most of these programs use optimization

methods that may fail to optimize these models properly. Even when they do converge, there is no assurance that they

have found the global optimum, and it just might be a good approximation of the global minimum. In this research a

heuristic optimization algorithm, simulated annealing (S.A), has been tested for estimating the parameters of a Logit

model for a mode choice problem that had 17 parameters for the city of Isfahan and has been compared with the same

model calculated using GAUSS that uses common and conventional algorithms. Simulated annealing is and algorithm

capable of finding the global optimum and also it’s less likely to fail on difficult functions because it is a very robust

algorithm and by writing the computer program in MATLAB the estimation time has been decreased significantly. In

this paper, this problem has been briefly discussed and a new approach based on the simulated annealing algorithm

to solve that is discussed and also a new path for using this technique for estimating Nested Logit models is opened

for future research by the authors. For showing the advantages of this method over other methods explained above a

case study on the mode choice of Isfahan has been done.

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In this paper, a new approach was presented for bus network design which took the effects of three out of four stages of the bus planning process into account. The presented model consisted of three majors steps 1- Network Design Procedure (NDP), 2- Frequency Determination and Assignment Procedure (FDAP), and 3- Network Evaluation Procedure (NEP). Genetic Algorithm (GA) was utilized to solve this problem since it was capable of solving large and complex problems. Optimization of bus assignment at depots is another important issue in bus system planning process which was considered in the presented model. In fact, the present model was tested on Mandl’s bus network which was a benchmark in Swiss network and was initially employed by Mandl and later by Baaj, Mahmassani, Kidwai, Chakroborty and Zhao. Several comparisons indicated that the model presented in this paper was superior to the previous models. Meanwhile, none of the previous approaches optimized depots assignment. Afterwards, sensitivity analysis on GA parameters was done and calculation times were presented. Subsequently the proposed model was evaluated thus, Mashhad bus network was designed using the methodology of the presented model.