The Berth Allocation Problem (BAP) is one of the most critical and widely studied problems in port operations. While significant contributions have been made in the use of operations research methods and techniques to solve the BAP in container terminals, almost no attention has been directed to bulk ports. In this paper, we study the berth allocation problem in bulk ports 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 that it is necessary to account for the cargo type on the vessel. In our model, the cargo locations on the yard and the locations of the fixed facilities such as conveyors and pipelines along the quay are explicitly taken into consideration in modeling the handling times of the 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. For a given yard layout of the bulk terminal and given locations of fixed facilities such as conveyors and pipelines along the quay, our model enhances coordination between berthing and yard activities. We present a mixed integer linear programming (MILP) 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. Our research problem derives from the realistic requirements of the port where currently the waiting times for the vessels are very large. The results indicate that the set partitioning approach and the heuristic approach can be used to obtain near-optimal solutions for even larger problem size.2

In this research we study the berth allocation problem (BAP) in real time as disruptions occur. In practice, the actual arrival times and handling times of the vessels deviate from their expected or estimated values, which can disrupt the original berthing plan and potentially make it infeasible. We consider a given baseline berthing schedule, and solve the BAP on a rolling planning horizon with the objective to minimize the total realized costs of the updated berthing schedule as the actual arrival and handling time data is revealed in real time. The uncertainty in the data is modeled by making appropriate assumptions about the probability distributions of the uncertain parameters based on past data. We present an optimization based recovery algorithm based on set partitioning method and a smart greedy algorithm to reassign the vessels in the events of disruption. Our research problem derives from the real world issues faced by the SAQR port, Ras Al Khaimah, UAE, where the berthing plans are regularly disrupted owing to a high degree of uncertainty in information. A simulation study is carried out to assess the solution performance and efficiency of the proposed algorithms, in which the baseline schedule is chosen as the solution of the deterministic berth allocation problem without accounting for any uncertainty. Results indicate that the proposed algorithms can significantly reduce the total realized costs of the berthing schedule as compared to the ongoing practice of reassigning vessels at the port.2

Exact and heuristic approach methods to solve berth allocation problem in bulk ports. Tech. rep., TRANSP-OR, Ecole Polytechnique Federale De Lausanne, 2012. Zhen, L. An integrated model for berth template and yard template planning in transshipment hubs. Transportation Science 45 (2011), 483-504.

et mots-clésLes trains qui transportent des conteneurs empilés (en deux niveaux) sont unélément important du réseau de transport nord-américain. Le problème de chargement des wagons correspond un problème opérationnel couramment rencontré dans les terminaux ferroviaires. Elle consiste optimiser l'affectation des conteneurs des emplacements spécifiques sur les wagons.Ce mémoire est centré sur un article scientifique traitant le chargement optimal publié dans

We present an optimization-based decision support system to generate optimal aircraft engine maintenance schedules that reflect qualitative and quantitative trade-offs from customer, business, and shop perspectives. The approach is currently implemented at GE Aviation Services for global overhaul network induction planning for all commercial product lines.