Allium assadii Seisums is described as a new to science and Allium hollandicum R.M.Fritsch is reported for the first time from Iran. Distributional and taxonomical notes are given on A. jesdianum Boiss. & Buhse, A. kazerouni Pars a, A. altissimum Regel, and A. pseudozeravschanicum M.Pop. & Vved.ex B.Fedtsch.& M. Pop.

Container terminals are places where freights are moved by special equipment. One of the most important issues in seaside operation scheduling in container ports is BERTH scheduling so that the BERTH plan has a great influence on the quay crane schedule, the yard storage plan and even the truck routing. In this paper, a mix integer linear programming model is proposed for dynamic and hybrid BERTH scheduling problem to schedule multiple vessels at multiple terminals at the Shahid-Rajaei container port. To evaluate the proposed model, the results of the present port operation in Shahid Rajaei port are compared with the results of the proposed model. The results reveal that the proposed model has decreased the vessels departure delay up to 50 percent in container port. The proposed model is evaluated by comparing the results with discrete BERTH scheduling model in literature. Numerical examples show that applying the proposed BERTH scheduling model can improve operations and significantly decrease vessel delayed departures compared with discrete BERTH scheduling model. So, in competition with other nearby ports, the container port can be more successful in satisfying the shipping companies and have higher productivity and profitability.

The most important objective of a container terminal is to increase the efficiency and to decrease the turnaround time. Turnaround time depends on the optimal allocation and scheduling of terminal resources including BERTHs, trucks, cranes, and yards. Therefore, optimal allocation and scheduling of the terminal resources could be considered as one of the most effective methods to increase the efficiency. BERTHs are the most important resources of the container ports, because their construction is more costly than all other cost items. Therefore, optimal use of BERTHs is a key factor for increasing the efficiency of container terminals. The objective of optimal allocation of BERTHs is to reduce the container processing costs in the ports. This index is a proper one for measuring the effectivity and efficiency of container terminals. This article tries to analyze the BERTH allocation as a model for minimizing servicing time to ships. The most important limitation of this study is the non-equality of ship processing time in various BERTHing points. This time variation depends on the distance between the BERTHing points and stacking areas in the yard.

Ports are important hubs that connect maritime transport to other modes. For this reason, ports are considered important infrastructures for freight transportation, trade, and the global economy. Therefore, optimizing port plans and operations will play a significant role in port costs and revenues. BERTH planning is part of port operations that includes two problems; BERTH Allocation Problem (BAP) and Quay Crane Assignment Problem (QCAP). The optimal solution to these two problems can affect the freight transportation speed and cost. This paper integrated modeling two problems BAP and QCAP, and solved them using four metaheuristic algorithms (GA, ICA, TS, ACO). Whereas BERTH planning is in a disrupted environment and unforeseen events may occur during the program's execution, incurring additional costs for the port, or even stopping the initial plan execution, rescheduling the original BERTH plan is necessary. This paper uses two methods (global and local rescheduling) with metaheuristic algorithms to find the optimal method for BERTH rescheduling. Numerical analysis shows the proper performance of GA and ICA algorithms in solving the initial BERTH planning model and the global rescheduling method. In contrast, for local rescheduling, the ACO algorithm has better performance. Evaluation and validation of models and methods of solving this paper are done using the data of ships' arrival and departure in Shahid Rajaei port.

To minimize the total time spend for servicing the ships, this article tries to assess BERTH allocation in form of Mixed-Integer Non-Linear Programming Model. Further, to validate the proposed model, this article has used outputs of Imai model. Results of the study illustrate that due to the low number of non-linear variable in proposed model in compare with Imai model, achieving the model output take a shorter time using proposed model instead of Imai model.

This study aimed to estimate the genetic parameters of body WEIGHT traits in Markhoz goats, using B-spline random regression models. The data used in this study included 19549 records collected during 29 years (1992-2021) in Markhoz goat Breeding Research Station, located in Sanandaj, Iran. The model used to analyze data included fixed effects (year of birth, sex, type of birth and age of dam) and random effects including direct additive genetic, maternal additive genetic, permanent environmental and maternal permanent environmental assuming homogeneous and heterogeneous residual variance during the time. Akaike (BIC) and Bayesian (BIC) information criteria were used to compare the models and bspq.4.4.4.4 was selected as the best model. The direct heritability values for birth, 3-month, 6-month, 9-month and 12-month WEIGHTs were estimated to be 0.14, 0.16, 0.08, 0.28 and 0.26, respectively. Genetic correlation between body WEIGHTs at birth and 3-month, birth and 6-month, birth and 9-month, birth and 12-month, 3-month and 6-month, 3-month and 9-month, 3-month and 12-month, 6-months and 9-month and 9-month and 12-month were 0.22, 0.38, 0.21, 0.56, -0.26, 0.30, 0.62, 0.86 and 0.77, respectively. The highest phenotypic correlation was between the WEIGHT of 9-month and 12-month (0.82) and the lowest correlation was between birth WEIGHT and 3-month and 6-month (0.12). The results showed that the 9-month WEIGHT is a good criterion for selection in Markhoz goats.