A hybrid genetic algorithm with a new packing strategy for the three-dimensional bin packing problem

Kang, Kyungdaw; Moon, Ilkyeong; Wang, Hongfeng

doi:10.1016/j.amc.2012.07.036

Cited by 43 publications

(15 citation statements)

References 13 publications

(15 reference statements)

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“…The graphs in Fig. (4) shows the search history of average obtained values of 25 sub-problems for each data set class in the average bin usage ratio (BUR) obtained by the basic ABC algorithm and proposed approaches, and Table 2 shows performance of the three approaches on the generated data set. The search history of each class is statistically analyzed for the basic ABC and the proposed approaches by using one-way ANOVA and Fisher's Least Significant Difference (LSD) post hoc test.…”

Section: Computational Results and Discussionmentioning

confidence: 99%

“…First part of 3D-BPP researches focused on to improve the mathematical modellings [2] for better item allocation approach, the second part of the researches proposed solution approaches [3] for variable bin packing conditions and constraints, and the last part of the researches has improved the item allocation orders with heuristic methods [4]- [6] to provide better solutions compared to the integer-based programming approaches.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Effects of memory and genetic operators on Artificial Bee Colony algorithm for Single Container Loading problem

Bayraktar

Ersöz

Kubat³

2021

Applied Soft Computing

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The Artificial Bee Colony (ABC) algorithm is widely used to achieve optimum solution in a short time in integer-based optimization problems. However, the complexity of integer-based problems such as Knapsack Problems (KP) requires robust algorithms to avoid excessive solution search time. ABC algorithm that provides both the exploitation and the exploration approach is used as an alternative approach for various KP problems in the literature. However, it is rarely used for the Three-Dimensional Bin Packing Problem (3DBPP) which is an important part of the transportation systems. In this study, the exploitation and exploration aspects of the ABC algorithm are improved by using memory mechanisms and genetic operators to develop two different hybrid ABC algorithms. The developed algorithms and the basic ABC algorithm are applied to a generated 3DBPP dataset to observe the effects of the memory mechanism and the genetic operators separately. The results show that the genetic operators are more effective than the memory mechanism to develop a hybrid ABC algorithm, for solving heterogeneous 3DBPPs.

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Section: Computational Results and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effects of memory and genetic operators on Artificial Bee Colony algorithm for Single Container Loading problem

Bayraktar

Ersöz

Kubat³

2021

Applied Soft Computing

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“…In this work, they also gave a clear definition of the Container Stowage Problem for Below Deck Locations (CSPBDL), and constructed the Constraint Programming (CP) and Integer Programming (IP) models. Kang et al [10] proposed a hybrid genetic algorithm for the three-dimensional bin packing problem to maximize the number of containers loaded onto a ship. Salido et al [18] proposed a decision support system for the Container Stacking Problem (CSP), the Berth Allocation Problem (BAP) and the Quay Crane Assignment Problem (QCAP).…”

Section: Jian Jin and Weijian MImentioning

confidence: 99%

An AIMMS-based decision-making model for optimizing the intelligent stowage of export containers in a single bay

Jin¹,

Mi²

2019

Discrete &Amp; Continuous Dynamical Systems - S

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Stowage operations in container terminals are an important part of a port's operational system, as the quality of stowage operations will directly affect the efficiency of port loading and discharge operations, and the scheduling of container shipping liners. The intelligent stowage of containers in container ships was studied in this work. A multi-objective integer programming model was constructed with the minimization of container rehandling, yard crane movements, and the sum of weight differences between stacked container pairs as its objective functions, to address the need for intelligent optimization of single bay export container stowage on a ship's deck. This model also satisfies the stability requirements of preliminary stowage plans drawn by shipping companies, and the operational requirements of container terminals. Linear computational methods were then constructed to transform non-linear constraints into linear ones for better AIMMS solution. Through numerous case analyses and systematic tests, it was shown that our system is able to rapidly solve for stowage planning optimization problems with complex preliminary stowage data, thus proving the applicability and effectiveness of this model. In particular, the application of this model will simultaneously address the safety of ship voyages, the transportation quality of shipping containers and other forms of cargo, and the cost efficiency of ship operations. In addition, this model will also contribute to the optimization of loading and discharge processes in container terminals. Therefore, our model has immense practical value for improving port productivity, as it will contribute to the organization of port operations in a rational, orderly and effective manner.

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“…This heuristic has gained its popularity in various works e.g. [6,25,26]. This heuristic always searches for a space with the minimal x (deepest) coordinate to place the current item.…”

Section: Online Packing Heuristicmentioning

confidence: 99%

An Online Packing Heuristic for the Three-Dimensional Container Loading Problem in Dynamic Environments and the Physical Internet

Nguyen

Bui

et al. 2017

Applications of Evolutionary Computation

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A hybrid genetic algorithm with a new packing strategy for the three-dimensional bin packing problem

Cited by 43 publications

References 13 publications

Effects of memory and genetic operators on Artificial Bee Colony algorithm for Single Container Loading problem

Effects of memory and genetic operators on Artificial Bee Colony algorithm for Single Container Loading problem

An AIMMS-based decision-making model for optimizing the intelligent stowage of export containers in a single bay

An Online Packing Heuristic for the Three-Dimensional Container Loading Problem in Dynamic Environments and the Physical Internet

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