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

Abstract

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

Using a Hybrid Model on Joint Scheduling of Berths and Quay Cranes—From a Sustainable Perspective

“…Finally, a large number of experiments have shown this heuristic algorithm to be superior and proven the feasibility of using a genetic algorithm to solve berth scheduling in a dynamic environment. Umang et al [39] used precise and heuristic algorithms for berth allocation in discrete ports. Lee et al [31] proposed an improved genetic algorithm in order to obtain an approximate optimal solution.…”

Real-time management of berth allocation with stochastic arrival and handling times

“…The deterministic berth allocation problem (BAP) in bulk ports with dynamic vessel arrivals and hybrid berth layout is studied by Umang et al (2013).…”

“…We assume a hybrid berthing layout and a fixed planning horizon partitioned into discrete time buckets, where each vessel may occupy multiple discrete berth sections, but a given section may be occupied by at most one vessel at a given time, as shown in Figure 1. Figure 1: Hybrid berthing layout, showing a feasible assignment of vessels to berth sections at a single point in time Umang et al (2013) demonstrates that the dynamic hybrid berth allocation problem with known arrival and handling times can be effectively modeled and solved as a generalized set-partitioning problem (GSPP) for relatively large problem size and time horizon of few days. In this approach, the set of all feasible single-vessel berthing assignments is generated a priori and is denoted by the set P. Note that a berthing assignment for a single vessel specifies the berth sections that will be occupied by the vessel, its berthing time, and its completion time (equal to the berthing time plus the handling time).…”

“…The underlying model is the dynamic, hybrid berth allocation model for bulk ports developed by Umang et al (2013). We consider uncertainty in both the arrival times and the handling times of the vessels.…”

Decentralized Cooperative Metaheuristic for the Dynamic Berth Allocation Problem

“…Depending on how the quay is modelled, the BAP can be referred to as discrete (the quay is divided into segments called berths) or continuous (the quay is not divided, thus the vessels can berth at any position in the quay). Moreover, in some related works (e.g., [5], [14]) there is also a hybrid consideration of the quay (the quay is divided into a set of berths and a vessel can occupy more than one berth at a time or share its assigned berth with other container vessels). Depending on the arrival time, the BAP can be classified into static (the vessels are already in port when the berths become available) or dynamic (the vessels arrive during the planning horizon).…”