Yard crane scheduling in a container terminal for the trade-off between efficiency and energy consumption

He, Junliang; Huang, Youfang; Yan, Wei

doi:10.1016/j.aei.2014.09.003

Cited by 110 publications

(54 citation statements)

References 40 publications

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“…He et al [28] addressed the problem of sharing internal trucks among multiple container terminals considering transportation energy consumption. In order to reduce energy consumption of yard crane, He et al [29] revealed negatively correlated relationship between the energy-saving and high efficiency of yard crane scheduling problem, and provided an appropriate approach for balancing the two objectives. Similarly, the integrated handling equipment scheduling model for minimizing energy consumption was formulated by He et al [30].…”

Section: Literature Reviewmentioning

confidence: 99%

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Berth allocation and quay crane assignment in a container terminal for the trade-off between time-saving and energy-saving

2016

Advanced Engineering Informatics

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Section: Literature Reviewmentioning

confidence: 99%

“…Constraints (28) ensure that the number of QCs assigned to a vessel must not be greater than its maximum number of QCs allowed to serve simultaneously. Constraints (29) ensure that no QC is assigned to a vessel after it departs. Constraints (30) ensure that no QC is assigned to a vessel before it is moored at the berth.…”

Section: T Bpsmentioning

confidence: 99%

Berth allocation and quay crane assignment in a container terminal for the trade-off between time-saving and energy-saving

2016

Advanced Engineering Informatics

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“…Stacking crane scheduling is one of the main parts of planning container terminal activities, and there has been a rapid growth of research in this area over the last decade. Comprehensive literature reviews of problems, models and solution methods in storage yard operations of a container terminal are provided by Stahlbock and Voß , Kemme , Carlo, Vis, and Roodbergen , Gharehgozli et al , He et al , Li et al , Wu et al , van Dijk , Kaveshgar and Huynh , Shu et al and Boysen et al .…”

Section: Introductionmentioning

confidence: 99%

A note on scheduling container storage operations of two non‐passing stacking cranes

2017

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We study a scheduling problem for a container block, in which there are incoming containers only. Container placement is served by two non‐passing stacking cranes based at the opposite sides of the container block. The same time is required for any crane to move between two adjacent bays of the container block and the same different time is required for any crane to perform any down‐and‐up operation related to container lifting at the pick‐up point or container lowering at the storage point. Containers are assigned to the cranes according to one of the following policies: (1) two fixed sequences policy where a container processing sequence is given for each crane, (2) dedicated crane policy where containers are preassigned to the cranes, (3) one fixed, one arbitrary sequence policy where a container processing sequence is given for one crane and it can be arbitrary for the other crane, (4) flexible policy where any container can be assigned to any crane at any time, and (5) global fixed sequence policy where the container sequence is given and the relative processing order of containers in this sequence must be preserved by any crane. The objective is to minimize the completion time of the latest operation. We show that the problem is polynomially solvable for policy 1 and, if the number of containers to be placed in the same bay is no more than a half of all containers, for policy 4. It is NP‐hard in the strong sense for policies 2 and 3. Approximation algorithms with guaranteed absolute and relative deviations from the optimum are devised for policies 4 and 5. The results translate for the case of outgoing containers only.

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“…When the value is small, it is helpful for the particle to search carefully in the current area. In this paper, the inertia weight factor used the decreasing strategy to achieve the goal of optimization, and the formula is shown in formula (19) …”

Section: Adjustment Of Inertia Weight Factor mentioning

confidence: 99%

Research on Location Problem of Multi-distribution Center based on Chaos Adaptive Mutation Particle Swarm Optimization Algorithm

Du¹,

Wu²,

Wang³

2016

IJGDC

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Location problem of multi-distribution center is a kind of NP hard problem. To solve such problems, this paper proposes a chaos adaptive mutation particle swarm optimization algorithm. The algorithm uses the ergodic property of chaos to initialize the particle swarm to enhance the diversity of the population, according to the variance of population fitness to adjust the probability of mutation, and adjust the inertia weight factor to improve the global and local search capability of the whole population. In this paper, the algorithm is applied to the location problem of multi-distribution center, established the multi-factor constraints of mathematical model which aiming at timeliness, and on this basis, the corresponding algorithm is designed. It can be seen from the location instance simulation results that the optimization results and efficiency of the adaptive mutation particle swarm optimization algorithm is better than the genetic algorithm and the standard particle swarm optimization algorithm.

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Yard crane scheduling in a container terminal for the trade-off between efficiency and energy consumption

Cited by 110 publications

References 40 publications

Berth allocation and quay crane assignment in a container terminal for the trade-off between time-saving and energy-saving

Berth allocation and quay crane assignment in a container terminal for the trade-off between time-saving and energy-saving

A note on scheduling container storage operations of two non‐passing stacking cranes

Research on Location Problem of Multi-distribution Center based on Chaos Adaptive Mutation Particle Swarm Optimization Algorithm

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