A cost based approach for a Crane Assignment and Scheduling Problem

Abstract

Different methods are used to address Quay Crane Assignment and Scheduling Problems (QCASP). In current literature often the unloading time is used to optimize QCASPs. However, this approach neglects the value of the vessel's freight. This paper therefore uses a cost based approach to optimize container terminal operations, which allows the model to focus on two objectives. The first objective is to show the impact of varying freight lead time costs on the priority of vessels and consequently the Quay Crane (QC) assignment and scheduling. The second objective is to implement adjustable QC operation costs and working rate and show the impact of particular adjustments. The model results show vessel prioritization based on the value of the vessel's freight. The variation in crane operation cost only impacts the assignment and scheduling in the occurrence of high crane operating costs relative to the value of the vessel's freight.

An integrated berth allocation and yard assignment problem for bulk ports: Formulation and case study

“…Constraints (26) ensure that a cargo location p must be assigned to one vessel at any time step to avoid any congestion. Constraints (27) ensure that yard locations are dedicated to cargo types, and only one cargo type can be assigned to a yard location at any time. Constraints (28) take into account the assignment of a vessel to a yard with the required cargo type.…”

“…Port operators are faced with the decision of expanding resources or maximizing the utilization of existing ones. Obviously, the latter is a more cost-effective option and it is enabled with the help of optimization [27]. Optimization techniques are thus increasingly implemented in port operations, which can be distinguished into two main areas, namely seaside and yardside operations [9].…”

On the Berth Allocation Problem

“…Relaxing too many simplifying assumptions will render the problem extremely difficult to solve, if not impossible, due to high complexity and thus, solving it would be very time consuming. On the other hand, not considering enough circumstances will render the result unrealistic, despite reducing complexity and solving time to an absolute minimum [21]. Several works have been developed that address the BAP, each with a varying level of complexity and different assumptions.…”