Due to the continuously increasing container trade, many terminals are presently operating at or close to capacity. An efficient terminal is one that facilitates the quick transshipment of containers to and from ships. In this sake, this paper addresses the ship assignments problem at a maritime container terminal, where ships are normally assigned to specific quay cranes until the work is finished. The paper’s target is to develop a new Continues Berth Allocation Problem (CBAP) in the form of a mixed integer nonlinear programming to achieve the best service time in a container terminal. For illustrating the accuracy of Proposed model (PM), Imai et. al. 's model (IM) (TRANSPORT RES B, 39 (2005) 199–221) was applied and a wide variety of computational test examples were conducted. The results of demonstrated that the presented BAPC reduces the number of nonlinear variables (constraints) and generates substantial savings in the CPU time.

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.

Failure rate curve based on the failure rate function of many electrical and mechanical systems shows a bathtub-shape form. In the first phase of this curve, where the failure rate has a decreasing form with a high slope, manufacturers use the burn-in method to eliminate defective products before reaching the market. In this phase most of the failures are minor (since the component is completely new, this type of error generally takes happen because of bad assembling, displacement of a socket, and so on) or major type failures (for example because of wrong design, selecting unsuitable raw materials, and so on). In the second phase, where the failure rate curve shows a constant value, manufacturers offer warranty services to their customers to ensure them about the quality and performance of their products. In this paper, we investigate the total cost incurred during the burn-in and warranty periods from the manufacturer's point of view. We consider different types of repair services and obtain the expected total cost in each phase. We present an optimization example to illustrate the efficacy of the proposed model in finding optimal values for burn-in and warranty periods.

In many signal processing applications, such as EEG analysis, the non-stationary signal is often required to be segmented into small epochs. This is accomplished by drawing the boundaries of signal at time instances where its statistical characteristics, such as amplitude and/or frequency, change. In the proposed method, the original signal is initially decomposed into signals with different frequency bands using wavelet transform. The fractal dimension of the decomposed signal is calculated in a sliding window and the results are used as a feature for adaptive segmentation. A criterion is introduced in this paper to choose a proper length for the sliding window. Performance of the proposed method is compared with that of three other existing segmentation methods using synthetic and real EEG data. Simulation results show the high efficiency of the proposed method in signal segmentation.

This paper employs nonlinear programming (NLP), genetic algorithm (GA), and fixed length gene genetic programming (FLGGP) for the real-time operation of a three-reservoir system (Karoon4, Khersan1, and Karoon3 reservoirs) in which dependent and independent approaches are used to forecast the hydroelectric energy generated by the system. Unlike the forecast-independent approach, in the forecast-dependent approach, the value of release in each period depends on the reservoir in flow of the same period. Moreover, nonlinear decision rule (NLDR) curves are considered, and the total deficiency function as well as efficiency criteria are used to investigate the results of each procedure used. Finally, the performances of real-time operation of single- and three-reservoir systems are investigated and compared. Results indicate that the FLGGP gives the most efficient function for the extraction of reservoir operation rules in both the approaches examined. Comparison of the forecast-dependent and independent approaches revealed no significant differences. Therefore, the forecastindependent approach may be recommended for application in the extraction of reservoir operation rules due to its simplicity and ease of application.

In a walking cycle design, maximizing the upright balance should be considered in addition to the kinematic constraints, energy consumption rate must be considered. The purpose of this study is to find the optimal step length obtained for each person according to the physical features. In this research, in order to minimize energy consumption rate by considering maximum balance two cost function were defined. the fall cost function was designed based on the concept of MOS and balance index. To investigate the upright balance and to reconstruct the movement pattern, Data from normal walking gait of healthy subjects was taken and seven links model was defined. In this study, the optimal step length was obtained for the person with height, weight and gait cycle characteristics. it is shown that for a person of 92kg mass and 1. 87 meters height, the best step length in walking would be 0. 54 meters. In this study, the kinematic and kinetic characteristics of human motion were identified by the analysis of gait patterns on a treadmill. Through the calculation of the balance index, individuals are helped to find the optimal step length for which the maximum balance is achieved. The results of the study can provide the optimal step length to correct the gait pattern.

Sliding window is one of the road network screening methods to identify black spots. There are two parameters which are required to be defined by the user: the window length and the minimum number of crashes per black spot. Based on previous studies, changing the window length significantly affects the process of black spots identification. In other words, changing window length and increment length leads to different results. The reviews show that, window length and increment length are selected based on engineering judgment or using the previous experiences, and statistical techniques and scientific methods have not been used. In this research, a new method is proposed based on optimizing the framework of the sliding window method by examining its features. The new method allows the sliding window length to be estimated dynamically. The optimization methodology is as follows: First, the desired road is segmented and for each segment, several different scenarios of window length are selected using the density-based clustering algorithm. Then the safety performance function is developed and the number of predicted and expected accidents and the difference between them as the potential safety improvement is calculated for each window movement for all selected scenarios in the segment. Finally, by calculating average differences using the analysis of variance, the length that has the lowest dispersion of difference values compared to the mean is determined as the optimal length of the window in each segment. The results of this study showed that in all segments, at least in a single movement of the window with the estimated optimal length, the SPF-value of the window has met the desired level of accuracy. Also, by moving the window with optimal dynamic lengths, 122 prone black spots identified, which has more crash density and effective length compared to the results of windows with fixed lengths of 300, 500 and 1000 meters.

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.