Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Reports, Documentation, and Standards
  4. Exact and heuristic methods to solve the berth allocation problem in bulk ports
 
report

Exact and heuristic methods to solve the berth allocation problem in bulk ports

Umang, Nitish  
•
Bierlaire, Michel  
•
Vacca, Ilaria  
2012

While significant contributions have been made in the use of operations research methods and techniques to optimize container terminals, relatively less attention has been directed to bulk ports. In this paper, we consider the problem of allocating vessels along the quay in a bulk port for hybrid berth layout and dynamic vessel arrivals. A key difference that distinguishes the berth allocation problem in bulk ports from that in container terminals is the presence of fixed specialized equipment facilities such as conveyors and pipelines at bulk ports. This has to be taken into consideration while modeling the handling times of vessels berthing at the port. The objective of the allocation is to minimize the total service time of all vessels berthing at the port in a given planning horizon. We present a mixed integer linear programming approach to model the problem, and an alternate exact solution approach based on generalized set partitioning. A heuristic approach based on the principle of squeaky wheel optimization is also presented. We compare the formulations from a computational perspective through extensive numerical experiments based on instances inspired from real data obtained from SAQR port, Ras Al Khaimah, UAE, the biggest bulk port in the middle east. The results indicate that the set partitioning approach and the heuristic outperform the MILP model, and can be used to obtain near-optimal solutions for even larger problem size.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

NitBierVac12.pdf

Access type

openaccess

Size

762.25 KB

Format

Adobe PDF

Checksum (MD5)

868a3b8ec89eca0eab887bd8bb93fceb

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés