An Integrated Berth Allocation and Resource Planning Problem in Bulk Ports

  • Safa I. Yousef

Student thesis: Master's Thesis


Maritime transportation has witnessed significant growth in the past decades, bringing benefits to consumers with relatively low transportation costs. The fast growing demand in this industry creates challenges in managing the available resources worldwide. Ports are the nodes of the world responsible for handling the sea-borne trade and providing space for vessels berthing to be serviced. While it is cost inefficient to build new berthing space, port operators utilize available resources by different techniques, one of which is the optimization of port operations research. From previous studies conducted on operations research, it is well established that the optimization has led to better resource utilization and, hence, to improved port efficiency. While a significant number of contributions have been directed towards the optimization of operations research in container terminals, little attention has been directed to bulk ports operations. In order to achieve a successful servicing plan in bulk ports, bulk operators are concerned with both wharf and yard management. Wharf operations include the berth allocation and scheduling plans, which significantly contribute towards the servicing time of vessels. The current direction in ports operations research is to utilize this resource by finding an optimal berthing plan. The cargo type must be explicitly known to bulk port operators, which in turn, requires the use of specialized equipment and loading (unloading) resources; therefore, the assignment of these resources shall be integrated to the optimal berthing plan in bulk ports. This thesis consists of modeling the Berth Allocation and Resource Planning (BARP) problem in bulk ports as a Mixed Integer Programing (MIP) problem. The problem is solved using Lagrangian Relaxation, and a Two Stage Iterative Solution Methodology (TSISM) is developed as an efficient heuristic to solve the same problem. The model is then tested by using real life data instances, and the solution methodologies are evaluated in terms of execution time and obtained results.
Date of AwardDec 2014
Original languageAmerican English
SupervisorAli Diabat (Supervisor)


  • Seaborne Industry
  • Berth Allocation
  • Resource Planning
  • Bulk Ports
  • Maritime Transportation.

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