Robust Scheduling for Berth Allocation and Quay Crane Assignment Problem

Decision makers must face the dynamism and uncertainty of real-world environments when they need to solve the scheduling problems. Different incidences or breakdowns, for example, initial data could change or some resources could become unavailable, may eventually cause the infeasibility of the obtained schedule. To overcome this issue, a robust model and a proactive approach are presented for scheduling problems without any previous knowledge about incidences. This paper is based on proportionally distributing operational buffers among the tasks. In this paper, we consider the berth allocation problem and the quay crane assignment problem as a representative example of scheduling problems. The dynamism and uncertainty are managed by assessing the robustness of the schedules. The robustness is introduced by means of operational buffer times to absorb those unknown incidences or breakdowns. Therefore, this problem becomes a multiobjective combinatorial optimization problem that aims to minimize the total service time, to maximize the buffer times, and to minimize the standard deviation of the buffer times. To this end, a mathematical model and a new hybrid multiobjective metaheuristic is presented and compared with two well-known multiobjective genetic algorithms: NSGAII and SPEA2+.

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Optimal berth allocation under regular and emergent vessel arrivals

Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment ◽

10.1177/1475090220937888 ◽

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.

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A HPSO for solving dynamic and discrete berth allocation problem and dynamic quay crane assignment problem simultaneously

Swarm and Evolutionary Computation ◽

10.1016/j.swevo.2015.11.002 ◽

2016 ◽

Vol 27 ◽

pp. 156-168 ◽

Cited By ~ 20

Author(s):

Hsien-Pin Hsu

Keyword(s):

Assignment Problem ◽

Allocation Problem ◽

Berth Allocation ◽

Berth Allocation Problem ◽

Quay Crane Assignment

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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.

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A GRASP-based metaheuristic for the Berth Allocation Problem and the Quay Crane Assignment Problem by managing vessel cargo holds

Applied Intelligence ◽

10.1007/s10489-013-0462-4 ◽

2013 ◽

Vol 40 (2) ◽

pp. 273-290 ◽

Cited By ~ 22

Author(s):

Mario Rodriguez-Molins ◽

Miguel A. Salido ◽

Federico Barber

Keyword(s):

Assignment Problem ◽

Allocation Problem ◽

Berth Allocation ◽

Berth Allocation Problem ◽

Quay Crane Assignment

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A New Genetic Algorithm for Continuous Berth and Quay Crane Allocation Problem

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.97-98.619 ◽

2011 ◽

Vol 97-98 ◽

pp. 619-622 ◽

Cited By ~ 1

Author(s):

Na Li ◽

Zhi Hong Jin ◽

Erick Massami

Keyword(s):

Genetic Algorithm ◽

Assignment Problem ◽

Container Terminal ◽

Allocation Problem ◽

Berth Allocation ◽

Improved Genetic Algorithm ◽

Berth Allocation Problem ◽

The Real ◽

Quay Cranes ◽

Quay Crane Assignment

The combined optimization of continuous berth allocation problem and quay crane assignment problem are solved. Considering the real constraints of container terminal, an improved genetic algorithm is proposed. The chromosome is composed of berthing time, berthing location and number of quay cranes. While in the following, specific quay cranes are fixed to assign to ships. Through comparisons with the former two literatures, the results are improved averagely by 33.78% and 28.57% respectively by the proposed genetic algorithm, which shows its effectiveness.

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