Background: Maritime transport from the beginning of human history, has played a fundamental role in shaping human societies and their economic development. In this era the communication arteries are the foundation of any country's economy. Due to the development of the necessary ports, coastal dredging activities in Iran had a growing trend during over the past two decades. However, from an environmental perspective less attention has been made particularly for the management of dredged material.. In this paper, the environmental risks of dredging operations were identified and ranked at Bandar Imam Khomeini.METHODs: The Delphi questionnaires were applied in order to initially create the important risk factors associated with dredging operations.. Then, multi-criteria decision making techniques were developed to calculate the likelihood of weighted index entropy measures, severity and likelihood of each risk has been detected, identified and prioritizes as significant risks using the Simple-additive-WEIGHTING (SAW) technique.Results: The results show that the size and concentration of petroleum hydrocarbons and heavy metals increased in aquatic organisms tissue and are noted as important risks as the first and second stress in the aquatic habitats. Creating of disorder in the context of the nature of bed sea during the dredging operations has also been ranked as the third factor.Conclusion: Primarily of dredging operations will ultimately lead to ecological imbalance, environmental risks and leads to disturbance in the location of the dredging.

MULTI-OBJECTIVE optimization plays an important role in modelling many problems. On the other hand, some of these problems deal with the optimization of the ratio of objectives, which are more important than the optimization of each objective alone. Since most of the real-world problems are faced with uncertainty in data and parameters, in this paper a class of MULTI-OBJECTIVE linear fractional programming problems with rough interval coefficients in the objective functions is considered. In order to deal with this group of problems, first the problem is taken out of the rough interval state, then the problem is solved using interval arithmetic and the weighted sum approach in MULTI-OBJECTIVE optimization. The obtained results are investigated in a numerical example.

In current study, multi objective programming (MOP) model was used for a representative farm in tropical zone of Dashtestan, Bushehr. Four goals were considered in the model namely, maximizing total gross margin (GM), minimizing irrigation water, risk, and used chemical fertilizer and pesticides. The model was solved by WEIGHTING and AUGMENTED e-constraint approaches in 18 and 42 various manners and a non-inferior solution obtained in each condition. The results indicated that, AUGMENTED e-constraint in comparison with WEIGHTING METHOD had less inadequacy and richer representation of the efficient set. Moreover, comparison of non-inferior solutions with farmer actual plan indicated that solutions in which goals of total GM maximization and minimization of risk have been emphasized were closer to actual plan.