Exact and Heuristic Methods for the Integrated Berth Allocation and Specific Time-invariant Quay Crane Assignment problems

In the operation of container terminal, berth allocation and quay crane assignment problems (BACAP) always prevent the container terminal from reducing time of ships in port and improving utilization of equipment. In this paper, the objective is to minimize total time of ships in port. Some reasonable and necessary hypotheses are proposed. The mathematical optimization model of BACAP based on the hypotheses is established. The genetic algorithm is used to solve the nonlinear programming model.

Download Full-text

A biased random-key genetic algorithm for the time-invariant berth allocation and quay crane assignment problem

Expert Systems with Applications ◽

10.1016/j.eswa.2017.07.028 ◽

2017 ◽

Vol 89 ◽

pp. 112-128 ◽

Cited By ~ 11

Author(s):

Juan Francisco Correcher ◽

Ramon Alvarez-Valdes

Keyword(s):

Genetic Algorithm ◽

Assignment Problem ◽

Berth Allocation ◽

Quay Crane Assignment ◽

Time Invariant

Download Full-text

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

Sustainability ◽

10.3390/su11072018 ◽

2019 ◽

Vol 11 (7) ◽

pp. 2018 ◽

Cited By ~ 2

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.

Download Full-text