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In this paper, the Resilience-Constrained Simultaneous Generation and Transmission Expansion Planning (RCGTEP) of the transmission network against natural disasters such as earthquakes and floods is presented. Therefore, the proposed scheme is modeled as a dual-objective problem, in which one objective function is to minimize the construction and operation costs of the resilient resources (RSs) and is considered, and in the other objective function, the expected energy not fed (EENS) due to the system outage against the aforementioned natural disasters will be formulated. Also, the proposed scheme is constrained by the AC optimal power distribution equations (AC-OPF), the planning and operation model of RSs such as generating units, robust transmission lines, series and parallel FACTS devices (SF and PF), and the resilience and angular stability constraints of the power system against earthquakes and floods in the presence of critical and non-critical loads. This strategy has uncertainty of RS availability under natural disaster conditions, so stochastic modeling will be adopted for RCGTEP. Finally, numerical results obtained by implementing the proposed strategy on IEEE standard transmission networks confirm the capabilities of this scheme in simultaneously improving economic indicators, utilization, angular stability and power system resilience.

In location-arc routing problems, unlike the well-known locating-routing problems, demand is on the arc and using deadheading arcs is permitted. Few studies have focused on this issue. In this research, a three-objective complex linear mathematical model for the multi-period location-arc routing problem under uncertainty with the time window is presented. The objectives of the model are included in the minimization of cost, cash-in-transit, and vehicle waiting time. The time window, minimizing cash-in-transit, and definition threshold for routes risk based on safety indicators, reduces the transportation risk indirectly. The proposed model is based on Bertsimas and Sim model and the ε-constraint method is used to solve 22 standard problems based on the proposed model. In addition, the robust model is validated with the realization model. The results show that the robust model versus deterministic model has better performs at higher conservatism levels and increases the uncertainty at each level of conservatism leading to higher costs.

Considering the importance of the proper arrangement of components and subsystems in space systems in order to satisfy the control, thermal and telecommunication system requirements, this article deals with the optimal placement design of a sample satellite. Compliance with condition control constraints, which is one of the basic system requirements of the satellite, is primarily defined as constraint. Other requirements of satellite subsystems, including the non-overlapping condition, are taken into account according to importance and priority. After determining the appropriate optimization method, the objective function and the constraints of the problem, the optimization algorithm is presented and the optimal answers are extracted. Due to the importance of controlling the issue of electromagnetic compatibility and preventing destructive damage caused by it, the proper wiring design is done on the optimal designs in compliance with the defined requirements.

This paper studies the autonomous vehicle leader following and collision avoidance problem. In this paper, like as a real car, geometric dimensions, mass and moment of inertia are considered for the car; steering-wheel and driving-wheel torques are the two control inputs. The nonlinear dynamics equation of the vehicle is derived. At first, an algorithm is proposed for changing the direction of the vehicle to follow the leader, then the suitable path for multiple obstacle avoidance and leader following is proposed, and then a nonlinear model predictive controller (MPC) is used to follow the reference trajectory. The desired trajectory is designed according to the elastic band method which is a powerful method for obstacle avoidance and leader following. The performances of the closed-loop system are illustrated through simulations. During the simulation the vehicle first changes its direction and then follows the leader without colliding with obstacles. Although the vehicle is inertial and non-holonomic in behavior, the simulations show that the two path planning methods with MPC scheme works well. For the future works the authors aim to solve the problem with moving obstacles.

Considering that the issue of choosing the passenger's route and the parameters involved in it has been the focus and study of transportation planners and policymakers for decades, in this article it has been tried to increase the computational efficiency and reduce the data processing time by examining and improving the mathematical model of passenger route selection in previous studies. This issue has been addressed through multi-core data processing (parallel processing) based on the modification of mathematical models presented in previous studies in the form of a public transport dynamic assignment model with the shortest path algorithm based on the schedule and the travel elimination sub-algorithm. The results were compared with the outputs of a non-dynamic model based on the shortest link-based algorithm to measure the effect of considering the capacity constraint and dynamics of the algorithm on the calculation time and the accuracy of the output. Even though the number of calculations went up by 13.7% compared to the basic model, the time it took to solve the problem went down by 20% because of parallel processing.