scholarly journals Multi-objective Berth Allocation Problem in a Multi-user Container Terminal with Consideration of Ship Service Priority

2001 ◽  
Vol 18 ◽  
pp. 721-728
Author(s):  
Etsuko NISHIMURA ◽  
Akio IMAI ◽  
Tomoko SAMURA
Keyword(s):  
Container Terminal ◽  
Allocation Problem ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Multi Objective ◽  
Service Priority

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.

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

scholarly journals A Hybrid GA with Variable Quay Crane Assignment for Solving Berth Allocation Problem and Quay Crane Assignment Problem Simultaneously

2019 ◽  
Vol 11 (7) ◽  
pp. 2018 ◽  
Author(s):  
Hsien-Pin Hsu ◽  
Tai-Lin Chiang ◽  
Chia-Nan Wang ◽  
Hsin-Pin Fu ◽  
Chien-Chang Chou
Keyword(s):  
Assignment Problem ◽  
Container Terminal ◽  
Allocation Problem ◽  
Container Terminals ◽  
Mutation Operator ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Fitness Value ◽  
Quay Crane Assignment ◽  
Time Invariant

Container terminals help countries to sustain their economic development. Improving the operational efficiency in a container terminal is important. In past research, genetic algorithms (GAs) have been widely used to cope with seaside operational problems, including the berth allocation problem (BAP) and quay crane assignment problem (QCAP) individually or simultaneously. However, most GA approaches in past studies were dedicated to generate time-invariant QC assignment that does not adjust QCs assigned to a ship. This may underutilize available QC capacity. In this research, three hybrid GAs (HGAs) have been proposed to deal with the dynamic and discrete BAP (DDBAP) and the dynamic QCAP (DQCAP) simultaneously. The three HGAs supports variable QC assignment in which QCs assigned to a ship can be further adjusted. The three HGAs employ the same crossover operator but a different mutation operator and a two-stage procedure is used. In the first stage, these HGAs can generate a BAP solution and a QCAP solution that is time-invariant. The time-invariant QC assignment solution is then further transformed into a variable one in the second stage. Experiments have been conducted to investigate the effects of the three HGA and the results showed that these HGAs outperformed traditional GAs in terms of fitness value. In particular, the HGA3 with Thoros mutation operator had the best performance.

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