In 2022, the FICO Xpress Best Paper Award was introduced to acknowledge exceptional research in Mathematical Optimization, Operations Research and related field. With a multitude of high-quality submissions, the scientific committee responsible for assessing the nominations faced the difficult task of selecting a runner-up paper. In this blog, we delve into the fascinating research conducted by Hamza Bouzekri and his coauthors, focusing on the intriguing realm of port logistics.
Maritime transport plays a pivotal role in global trade and the economy, making it the most significant mode of transportation worldwide. Ports serve as critical hubs within the maritime transit network, connecting shipping routes with road and rail networks on land. As the scale of maritime trade grows and congestion at ports increases, it becomes imperative to enhance port operation efficiency and maintain an organized and supervised port system.
The performance of port management is contingent upon both adhering to contractual clauses and making optimal use of port resources. There are substantial benefits to be gained from improving and optimizing port operations. The work by Bouzekri et al. (2021), published in the EURO Journal of Operational Research, addresses three interconnected decision problems concerning seaside operations at ports: the Laycan Allocation Problem (LAP), the Berth Allocation Problem (BAP), and the Quay Crane Assignment Problem (QCAP). Let’s first consider them all individually.
To enhance the realism of their model, the paper of Bouzekri et al. incorporates several rarely studied characteristics and constraints, including multiple quays, varying water depths, navigation channel restrictions related to tides, charter party clauses, and non-working periods. These constraints are modeled as predicates, which are logical expressions that evaluate to either "true" or "false." In the mathematical model, written in FICO Xpress Mosel, predicates are utilized to define and restrict the domain of an index, consequently determining the existence of a decision variable based on parameter values. Employing predicates allows for preprocessing the model using problem-specific data, resulting in a reduction of binary variables. This approach significantly improves computational performance, enabling the solution of practical-sized problems within a reasonable time frame using the MIP solver FICO Xpress.
The primary decision variable in the model is denoted as xvtqsqnq, which takes a value of 1 if vessel v starts berthing in time period t at section sq of quay q with nq assigned quay cranes, and 0 otherwise. The existence of this binary decision variable is subject to eight conditions. One such condition states that the draft of vessel v(Dv) must not exceed the water depth of its assigned berthing position sq in quay q(Wqsq): Dv≤Wqsq.
The decision variable xvtqsqnq exists only whenall the predicates are true. These predicates are implemented in the FICO Xpress Mosel modelling language as follows:
As a result of utilizing predicates extensively in the mathematical formulation of the model, the authors have achieved maximum flexibility in its implementation and significantly enhanced computational performance. By employing predicates, they have successfully reduced the number of decision variables upon problem instantiation. Moreover, this approach eliminates the need to introduce certain constraints into the model explicitly.
In conclusion, the extensive use of predicates in the mathematical model allowed to strike a balance between flexibility and computational efficiency. By leveraging the capabilities of the FICO Xpress Optimization suite, Bouzekri et al. have efficiently optimized the model and obtained the desired results.
We at FICO congratulate Hamza, Gülgün, and Vincent on being the runner-up in the FICO Xpress Best Paper Award. Their excellent work stood out among many strong contenders. Like many other research teams around the world, they are members of our Academic Partner Program. Join our FICO Xpress Optimization Community and learn about our free community licenses for everyone and our fully-fledged free licenses for all academics. The call for the 2023 edition of the FICO Xpress Best Paper Award is out now: Consider submitting your Xpress-related research paper!
Bouzekri, H., Alpan, G., & Giard, V. (2021). Integrated Laycan and Berth Allocation and time-invariant Quay Crane Assignment Problem in tidal ports with multiple quays. European Journal of Operational Research, 293(3), 892–909. https://doi.org/10.1016/j.ejor.2020.12.056
Maritime transport plays a pivotal role in global trade and the economy, making it the most significant mode of transportation worldwide. Ports serve as critical hubs within the maritime transit network, connecting shipping routes with road and rail networks on land. As the scale of maritime trade grows and congestion at ports increases, it becomes imperative to enhance port operation efficiency and maintain an organized and supervised port system.
The performance of port management is contingent upon both adhering to contractual clauses and making optimal use of port resources. There are substantial benefits to be gained from improving and optimizing port operations. The work by Bouzekri et al. (2021), published in the EURO Journal of Operational Research, addresses three interconnected decision problems concerning seaside operations at ports: the Laycan Allocation Problem (LAP), the Berth Allocation Problem (BAP), and the Quay Crane Assignment Problem (QCAP). Let’s first consider them all individually.
- The Laycan Allocation Problem (LAP) involves the tactical assignment of berthing time windows to vessels within a medium-term planning horizon, considering cargo availability and port resources. Solving the LAP supports the negotiation process between shipowners and charterers.
- The Berth Allocation Problem (BAP), also known as the Berth Scheduling Problem, focuses on the operational assignment of berthing positions and times to all vessels scheduled to be serviced within a short-term planning horizon, accounting for vessel and port constraints.
- The Quay Crane Assignment Problem (QCAP) deals with the operational assignment of quay cranes to each vessel scheduled for service within a short-term planning horizon, aiming to optimize their utilization. The assignment must adhere to the number of available cranes at the quay and the minimum and maximum crane requirements for each vessel.
To enhance the realism of their model, the paper of Bouzekri et al. incorporates several rarely studied characteristics and constraints, including multiple quays, varying water depths, navigation channel restrictions related to tides, charter party clauses, and non-working periods. These constraints are modeled as predicates, which are logical expressions that evaluate to either "true" or "false." In the mathematical model, written in FICO Xpress Mosel, predicates are utilized to define and restrict the domain of an index, consequently determining the existence of a decision variable based on parameter values. Employing predicates allows for preprocessing the model using problem-specific data, resulting in a reduction of binary variables. This approach significantly improves computational performance, enabling the solution of practical-sized problems within a reasonable time frame using the MIP solver FICO Xpress.
The primary decision variable in the model is denoted as xvtqsqnq, which takes a value of 1 if vessel v starts berthing in time period t at section sq of quay q with nq assigned quay cranes, and 0 otherwise. The existence of this binary decision variable is subject to eight conditions. One such condition states that the draft of vessel v(Dv) must not exceed the water depth of its assigned berthing position sq in quay q(Wqsq): Dv≤Wqsq.
The decision variable xvtqsqnq exists only whenall the predicates are true. These predicates are implemented in the FICO Xpress Mosel modelling language as follows:
As a result of utilizing predicates extensively in the mathematical formulation of the model, the authors have achieved maximum flexibility in its implementation and significantly enhanced computational performance. By employing predicates, they have successfully reduced the number of decision variables upon problem instantiation. Moreover, this approach eliminates the need to introduce certain constraints into the model explicitly.
In conclusion, the extensive use of predicates in the mathematical model allowed to strike a balance between flexibility and computational efficiency. By leveraging the capabilities of the FICO Xpress Optimization suite, Bouzekri et al. have efficiently optimized the model and obtained the desired results.
We at FICO congratulate Hamza, Gülgün, and Vincent on being the runner-up in the FICO Xpress Best Paper Award. Their excellent work stood out among many strong contenders. Like many other research teams around the world, they are members of our Academic Partner Program. Join our FICO Xpress Optimization Community and learn about our free community licenses for everyone and our fully-fledged free licenses for all academics. The call for the 2023 edition of the FICO Xpress Best Paper Award is out now: Consider submitting your Xpress-related research paper!
Bouzekri, H., Alpan, G., & Giard, V. (2021). Integrated Laycan and Berth Allocation and time-invariant Quay Crane Assignment Problem in tidal ports with multiple quays. European Journal of Operational Research, 293(3), 892–909. https://doi.org/10.1016/j.ejor.2020.12.056
Updated 3 years ago
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