Development of an Intelligent Hybrid Meta-Heuristic Allocation Model for Organizing the Dredging Vessels in Iranian Ports

Abstract

The organization of dredging ships has an important place in the operation of ports and maritime organizations. The main goal of the current research is to organize Iran’s dredging ships, considering risk management. This research uses artificial intelligence techniques in a Matlab programming environment to design a hybrid meta-heuristic model. The studied population of this research can be divided into two general groups: the first includes expert professors in industrial engineering, industrial management, port logistics management, and marine engineering (i.e., academic experts), and the second group comprises managers and professionals working in ports and maritime organization (i.e., industry experts). Their opinions were collected using a combination of non-probability targeted (judgmental) and snowball sampling methods in the spring of 2024. The main findings of this research are those of applying the research model to the country's dredging ships in Iran Ports and Maritime Organization, taking into account risk management, which is as follows the performance of reducing the time of dredging operations in various ports (I1) is equal to 0.07; the risk control aimed at increasing security in ports (I2) is equal to 0.10; marine traffic conditions improvement Index (I3) is equal to 0.06; allocation according to the number of existing dredges and their capacity (I4) is equal to 0.17; allocation according to the environmental conditions of the region (I5) is equal to 0.07 and allocation for reducing the cost of dredging projects in ports (I6) is equal to 0.13. These results, considering risk management, caused the organization of the country's dredging ships to be improved by 25%. Finally, suggestions are provided for the benefit of managers and professionals working in ports and maritime organizations as well as academic experts in fields like industrial engineering, industrial management, port logistics management, and marine engineering.