Price limits set up are adopted by many securities markets in countries such as the USA, Canada, Japan, and various other countries in Europe and Asia, to increase the stability of the financial market. These limits confine the price of the financial asset during any trading day to a range, usually determined based on the previous day's closing price. In this paper, we study the portfolio optimization problem while taking into account the price limit constraint. The dynamic programming technique is applied to derive the Hamilton– Jacobi– Bellman equation, and the method of Lagrange multiplier is used to tackle the constraint. Optimization problem solution results and numerical method show that the equilibrium path of wealth and investment in risky assets has a different pattern than the absence of price limits.

Various methods have been proposed to determine the ultimate pit limits. Artificial intelligence-based methods such as heuristic genetic algorithms, ants and colony competition algorithms. Artificial bee colony (ABC) algorithm is one of the most powerful heuristic algorithms inspired by the social life of bees. In this paper, a hypothetical example of the life of bees is primarily described to find the source with the highest amount of nectar by this algorithm. Then, a method based on the bee algorithm is proposed to determine the ultimate pit limit, and to examine its performance, a two-dimensional example is described step by step. In this example, it was found that in cases where the moving cone can not find the optimal ultimate pit limit, the ABC method is well suited for introducing solution. Then, this algorithm was used to determine the ultimate limits of Sungun Copper mine pit with a number of 120*100*45 blocks. To validate the proposed algorithm, the graph theory and moving cone techniques were used. Results showed that the profit obtained by ABC algorithm is just 1. 6% less than that of graph theory algorithm, which is a rigorous technique and entails finding the true optimum. Meanwhile, the ABC algorithm provides 12. 3% more profit when compared to heuristic moving cone algorithm.

In this Study، according to microfluidic structure and bio inspired techniques، a material detection sensor has been designed and fabricated based on micro fabrication method. The capacitive sensing has been designed numerically and optimized by a familiar multi physics software. In this type of sensor، a defined aptamer has been coated on the capacitor electrode surface and by flowing the fluid through the microchannel، the targeted material would be involved between the aptamer string structure and it makes a change in capacitor value. In this research، a novel readout system based on limit cycle has been introduced and implemented. In this method، a virtual nonlinear dynamic has been supposed beside the real system and makes the whole system behave in a limit cycle (LC). By measuring LC frequency and amplitude، capacitor value is estimated.

In this paper, a novel risk-based, two-objective (technical and economical) optimal reactive power dispatch method in a wind-integrated power system is proposed which is more consistent with operational criteria.  The technical objective includes the minimization of the new voltage instability risk index. The economical objective includes cost minimization of reactive power generation and active power loss. The proposed voltage instability risk employs a hybrid possibilistic (Delphi-Fuzzy)-probabilistic approach that takes into consideration the operator’s experience, the wind speed and demand forecast uncertainties when quantifying the risk index. The decision variables are the reactive power resources of the system. To solve the problem, the modified multi-objective particle swarm optimization algorithm with sine and cosine acceleration coefficients is utilized. The method is implemented on the modified IEEE 30-bus system. The proposed method is compared with those in the previously published literature, and the results confirm that the proposed risk index is better at estimating the voltage instability risk of the system, especially in cases with severe impact and low probability. In addition, according to the simulation results compared to typical security-based planning, the proposed risk-based planning may increase the security and economy of the system due to better utilization of system resources.

Objective Flexible Manufacturing Systems (FMS) are integrated workstations that utilize computer-controlled equipment components for production. These systems are managed by a central computer, which significantly enhances the efficiency and productivity of the production process. Accordingly, a case study is conducted on an FMS electrical manufacturing system with complex manufacturing processes, where automation on the production line is crucial. Selecting the optimal number of advanced equipment is a challenging and vital issue for managers aiming to boost productivity and efficiently fulfill customer orders. It is a hard-to-change model, and replacing equipment incurs substantial costs.   Methods This study employs the two-stage D-Optimal method to optimize the combination of FMS elements and equipment. The D-Optimal response level input is derived from discrete-event simulation results. Depending on the conditions, various FMS equipment is allocated to each process. Each simulation result for element combinations serves as input for the experimental design. Additionally, the response level (y) of experiments from various FMS indexes is calculated using a weighting method. To reduce the number of experiments and increase data accuracy in a case study with hard-to-change parameters, all combinations are categorized based on the number of automated and manual equipment. The two stages of the D-Optimal design are defined as follows: In the first stage, all combinations within these categories are investigated. In the second stage, the optimized combination from the first stage is analyzed to determine the best configuration. Experiments in the top category from the first stage are simulated and further evaluated in the second stage of the D-Optimal method.   Results In the first phase, all advanced production equipment and FMS elements were considered. After selecting the best-calculated “y” value, which was 147,133.09 in this category, another D-Optimal design was optimized in the second phase to determine the best combination. This combination yielded a “y” value of 151,317.88, representing an improvement over the best category in the first phase of the D-Optimal design. Consequently, the optimized combination from the first phase was further refined. The results from the developed D-Optimal method and the second phase indicate that the optimal combination of equipment involves using automated and FMS equipment for approximately 92.8% of the total components. Finally, a list of recommended FMS equipment is provided, and its productivity is compared with the productivity at the current level and a higher degree of automation for this production line.   Conclusion In summary, the results of the experimental design show that using advanced production systems does not necessarily improve system efficiency, and determining optimal combinations requires accurate calculations.

In order to study the spatial structure of oriental beech (Fagus orientalis Lipsky) stand at optimal stage, this research was carried out in the Caspian forests of Iran. The studied site consisted of a natural stand located at Sangdeh district (Mers-e-se) with three hectare area. It is located between 1900 and1950 m.a.s.l. Six sample plots each with 0.36 ha area, were systematically selected and all trees (1244 stem) within the plots were measured and recorded. Using increment borer, the mean age of the stand was estimated as 137 years; the age difference of trees was 40 years. Results showed that the stand has a closed canopy cover and distribution of stem number per diameter class was more or less homogenous (Bell shape) with a semi even-aged structure. Using Ripley's K function, the distribution of trees within the stand was random.

In this research, the famous multi-span highway bridge, which is based on the results of the previous researches of the authors, has a semi-isolated deck and optimized design specifications of the isolators and reinforced concrete piers have been considered. Using incremental dynamic analysis, by selecting two cases of displacement of the semi-isolated deck and displacement of the isolators or the shear strain of the isolators, the incremental dynamic analysis curves are obtained under the records proposed in FEMA P695. Then, while performing fragility analysis based on the results of incremental dynamic analysis, fragility curves are determined for the displacement of the semi-isolated deck and the displacement of isolators or the shear strain of the isolators in longitudinal and transverse directions of the bridge. Based on these curves, the values of the limit states for structural collapse, life safety, moderate damage, slight damage and first yield has been identified and proposed.