This work is devoted to a method of optimization of the composite shell woven reinforcements. This method is based on Goldenblat-Kopnov’s anisotropic model which is suitable for this material. This study involves three steps: Firstly, it is carried out experimental characterization of the strength properties of the material; then it is proposed a method of optimization of the winding angle of composite shell woven reinforcements based on the strength anisotropy of the material. The third step consist  in establishing the variation ranges of the static strength tensor components of this material in three planes of symmetry from the Sylvester’s criterion of positive definition of symmetric matrices. Obtained results allow improve the structural performance of composite shells with woven reinforcements.

The high speed is a very serious cause of accidents in the suburban traffic and both the financial and life damage is quite considerable. An approach to reduce speed is to install cameras to record the road traffic violations. Locating appropriate installation points can have a great role in the effectiveness of these systems. To this end, using the expert system, a model has been developed to locate cameras to record road traffic violations. It selects and introduces the best points from among the candidate points for the system installation considering all the desired items and considerations. In this model, first the qualitative information of the candidate points is converted into quantitative data and then the points are ranked based on the issues considered for each of them using the TOPSIS method. Lastly, the final highest ranking points are finalized and selected for the system installation at susceptible road sections including important entries/exits, distance from origin/destination, proper distance between two systems, and so on using the Goal Programming Approach.

Lack of sufficient container storage space, high land costs, and inadequate origin-destination accessibility of goods are the serious problems facing the coastal ports today due to the growing use of containers in the maritime transport. The most appropriate way to overcome these problems is to use the dry port concept as a multimodal transportation terminal with adequate distance from coastal ports and the main origins/destinations within the country.

Effort has been made in this research to model the dry port locating problem as a multimodal transportation terminal using the median P-hub location-allocation approach, and to be closer to the real-world conditions, the demand parameter has been assumed to be uncertain to propose a robust model resistant against uncertainty. Robust scenario-based optimization models have the potential to generate justified optimal solutions against the fluctuations of the problem's uncertain parameters. The data used in this model are the real ones from Iran Railway-Road Network.

Results of applying the proposed model show that Kerman, Fars, and North Khorasan provinces in Iran have the potential for dry port construction. The robust model's validation results presented at the end of the paper show 31% improvement in the model performance (output efficiency).