scholarly journals The tactical berth allocation problem with time-variant specific quay crane assignments

2021 ◽  
pp. 107168
Author(s):  
Emmanouil Thanos ◽  
Tulio Toffolo ◽  
Haroldo Gambini Santos ◽  
Wim Vancroonenburg ◽  
Greet Vanden Berghe
Keyword(s):  
Allocation Problem ◽  
Berth Allocation ◽  
Berth Allocation Problem

scholarly journals A Fuzzy Optimization Model for the Berth Allocation Problem and Quay Crane Allocation Problem (BAP + QCAP) with n Quays

2021 ◽  
Vol 9 (2) ◽  
pp. 152
Author(s):  
Edwar Lujan ◽  
Edmundo Vergara ◽  
Jose Rodriguez-Melquiades ◽  
Miguel Jiménez-Carrión ◽  
Carlos Sabino-Escobar ◽  
...  
Keyword(s):  
Optimization Model ◽  
Fuzzy Optimization ◽  
Optimal Solution ◽  
Allocation Problem ◽  
Berth Allocation ◽  
Triangular Fuzzy Numbers ◽  
Berth Allocation Problem ◽  
Arrival Times ◽  
Decision Variables ◽  
Short Time

This work introduces a fuzzy optimization model, which solves in an integrated way the berth allocation problem (BAP) and the quay crane allocation problem (QCAP). The problem is solved for multiple quays, considering vessels’ imprecise arrival times. The model optimizes the use of the quays. The BAP + QCAP, is a NP-hard (Non-deterministic polynomial-time hardness) combinatorial optimization problem, where the decision to assign available quays for each vessel adds more complexity. The imprecise vessel arrival times and the decision variables—berth and departure times—are represented by triangular fuzzy numbers. The model obtains a robust berthing plan that supports early and late arrivals and also assigns cranes to each berth vessel. The model was implemented in the CPLEX solver (IBM ILOG CPLEX Optimization Studio); obtaining in a short time an optimal solution for very small instances. For medium instances, an undefined behavior was found, where a solution (optimal or not) may be found. For large instances, no solutions were found during the assigned processing time (60 min). Although the model was applied for n = 2 quays, it can be adapted to “n” quays. For medium and large instances, the model must be solved with metaheuristics.

The dynamic berth allocation problem for a container port

2001 ◽  
Vol 35 (4) ◽  
pp. 401-417 ◽  
Author(s):  
Akio Imai ◽  
Etsuko Nishimura ◽  
Stratos Papadimitriou
Keyword(s):  
Allocation Problem ◽  
Berth Allocation ◽  
Container Port ◽  
Berth Allocation Problem

Optimal berth allocation under regular and emergent vessel arrivals

2020 ◽  
pp. 147509022093788
Author(s):  
Abbas Al-Refaie ◽  
Hala Abedalqader
Keyword(s):  
Waiting Time ◽  
Container Terminal ◽  
Allocation Problem ◽  
Container Terminals ◽  
Future Research ◽  
Satisfaction Level ◽  
Berth Allocation ◽  
Scheduling Problems ◽  
Berth Allocation Problem ◽  
Quay Crane Assignment

This research proposes two optimization models to deal with the berth allocation problem. The first model considers the berth allocation problem under regular vessel arrivals to minimize the flow time of vessels in the marine container terminal, minimize the tardiness penalty costs, and maximize the satisfaction level of vessels’ operators on preferred times of departure. The second model optimizes the berth allocation problem under emergency conditions by maximizing the number of assigned vessels, minimizing the vessel’s waiting time, and maximizing the satisfaction level on the served ships. Two real examples are provided for model illustration under regular and emergent vessel arrivals. Results show that the proposed models effectively provide optimal vessel scheduling in the terminal, reduce costs at an acceptable satisfaction level of vessels’ operators, decrease the waiting time of vessels, and shorten the delay in departures under both regular and emergent vessel arrivals. In conclusion, the proposed models may provide valuable assistance to decision-makers in marine container terminals on determining optimal berth allocation under daily and emergency vessel arrivals. Future research considers quay crane assignment and scheduling problems.

scholarly journals Modeling and solving the Tactical Berth Allocation Problem

2010 ◽  
Vol 44 (2) ◽  
pp. 232-245 ◽  
Author(s):  
Giovanni Giallombardo ◽  
Luigi Moccia ◽  
Matteo Salani ◽  
Ilaria Vacca
Keyword(s):  
Allocation Problem ◽  
Berth Allocation ◽  
Berth Allocation Problem

A New Memetic Approach to Solve the Strategic Berth Template Problem

2021 ◽  
Vol 12 (3) ◽  
pp. 212-231
Author(s):  
Issam El Hammouti ◽  
Azza Lajjam ◽  
Mohamed El Merouani
Keyword(s):  
Large Scale ◽  
Container Terminal ◽  
Mathematical Formulation ◽  
Population Based ◽  
Allocation Problem ◽  
Computational Time ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Simulating Annealing ◽  
Annealing Algorithm

The berth allocation problem is one of the main concerns of port operators at a container terminal. In this paper, the authors study the berth allocation problem at the strategic level commonly known as the strategic berth template problem (SBTP). This problem aims to find the best berth template for a set of calling ships accepted to be served at the port. At strategic level, port operator can reject some ships to be served for avoid congestion. Since the computational complexity of the mathematical formulation proposed for SBTP, solution approaches presented so far for the problem are limited especially at level of large-scale instances. In order to find high quality solutions with a short computational time, this work proposes a population based memetic algorithm which combine a first-come-first-served (FCFS) technique, two genetics operators, and a simulating annealing algorithm. Different computational experiences and comparisons against the best known solutions so far have been presented to show the performance and effectiveness of the proposed method.

Population-based Metaheuristics for the Dynamic Minimum Cost Hybrid Berth Allocation Problem

2021 ◽  
Vol 30 (04) ◽  
pp. 2150017
Author(s):  
Nataša Kovač ◽  
Tatjana Davidović ◽  
Zorica Stanimirović
Keyword(s):  
Container Terminal ◽  
Mathematical Formulation ◽  
Minimum Cost ◽  
Population Based ◽  
Allocation Problem ◽  
Maritime Transportation ◽  
Mixed Integer ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Metaheuristic Methods

This study considers the Dynamic Minimum Cost Hybrid Berth Allocation Problem (DMCHBAP) with fixed handling times of vessels. The objective function to be minimized consists of three components: costs of positioning, waiting, and tardiness of completion for all vessels. A mathematical formulation of DMCHBAP, based on Mixed Integer Linear Programming (MILP), is proposed and used within the framework of commercial CPLEX 12.3 solver. As the speed of finding high-quality solutions is of crucial importance for an efficient and reliable decision support system in container terminal, two population-based metaheuristic approaches to DMCHBAP are proposed: combined Genetic Algorithm (cGA) and improvement-based Bee Colony Optimization (BCOi). Both cGA and BCOi are evaluated and compared against each other and against state-of-the-art solution methods for DMCHBAP on five sets of problem instances. The conducted computational experiments and statistical analysis indicate that population-based metaheuristic methods represent promising approaches for DMCHBAP and similar problems in maritime transportation.

Fully Fuzzy Multi-objective Berth Allocation Problem

2020 ◽  
pp. 261-272
Author(s):  
Boris Pérez-Cañedo ◽  
José Luis Verdegay ◽  
Alejandro Rosete ◽  
Eduardo René Concepción-Morales
Keyword(s):  
Allocation Problem ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Multi Objective
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