An Evolutionary Algorithm Based Hyper-heuristic for the Set Packing Problem

Chaurasia, Sachchida Nand; Jung, Donghwi; Lee, Ho Min; Kim, Joong Hoon

doi:10.1007/978-981-13-0761-4_26

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…More artificial intelligence algorithm has achieved great results in many fields, including solving combinatorial optimization problems [14,15]. The intelligent optimization algorithm is an algorithm inspired by a certain phenomenon in nature, which mainly includes genetic algorithm [16], particle swarm algorithm [17], simulated annealing algorithm [18], and ant colony algorithm [19]. The artificial intelligence algorithm can cope with large bin packing problems and find better optimal solutions with low requirements for the expertise of the algorithm designer, but the convergence speed of the intelligent optimization algorithm is greatly affected by the initial solution and encoding method.…”

Section: Introductionmentioning

confidence: 99%

A 3D Offline Packing Algorithm considering Cargo Orientation and Stability

Wang

Gong

Zhao

et al. 2023

International Journal of Distributed Sensor Networks

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The box packing problem can be generalized as placing a batch of cargos with a specified number of different physical characteristics into a specified box. Suppose that a batch of cuboid cargos of different sizes are to be loaded into a batch of boxes of the same type, the cargos have constraints such as orientation and stability. Taking the mean value of the reciprocal of space utilization as the objective function, this paper designs a hybrid genetic algorithm that combines genetic algorithm and tabu search algorithm. Aiming at the information of the packing sequence and the rotating state of the box in the packing scheme, a two-stage real number encoding method and decoding method based on random keys are designed, and a crossover operation based on partial random keys and uniform crossover is designed. In order to convert the solution searched by the optimization algorithm into the actual packing scheme, a heuristic loading algorithm is designed while using the positioning rule of the lower left corner, the space selection rule of the minimum space, and the division and merging rules of the remaining space. In the early stage, the roulette method was used to strengthen the global search ability, and in the later stage, the optimal preservation strategy was used to speed up the algorithm convergence. To make up for the shortcomings of the genetic algorithm’s weak local search ability and slow convergence speed, the tabu search algorithm was used as a mutation operation in the genetic algorithm. The solution in the generation is used as the initial solution of the tabu search algorithm, and the search process is carried out. Finally, this paper tests the proposed hybrid algorithm on 6 groups of weakly heterogeneous and strongly heterogeneous data in the BR dataset. The results prove that the proposed algorithm can reduce the usage of boxes.

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Section: Introductionmentioning

confidence: 99%

A 3D Offline Packing Algorithm considering Cargo Orientation and Stability

Wang

Gong

Zhao

et al. 2023

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…EA/G [33] was a recently proposed evolutionary algorithm and was applied on random instances. Chaurasia et al presented an evolutionary algorithm-based hyperheuristic framework for solving the set packing problem [34]. Chaurasia and Kim proposed an evolutionary algorithm-based hyperheuristic framework that incorporates dynamic selection of parameters [35].…”

Section: Introductionmentioning

confidence: 99%

Solving the Set Packing Problem via a Maximum Weighted Independent Set Heuristic

Wang

et al. 2020

Mathematical Problems in Engineering

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The set packing problem (SPP) is a significant NP-hard combinatorial optimization problem with extensive applications. In this paper, we encode the set packing problem as the maximum weighted independent set (MWIS) problem and solve the encoded problem with an efficient algorithm designed to the MWIS problem. We compare the independent set-based method with the state-of-the-art algorithms for the set packing problem on the 64 standard benchmark instances. The experimental results show that the independent set-based method is superior to the existing algorithms in terms of the quality of the solutions and running time obtained the solutions.

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Hyper-heuristics: Autonomous Problem Solvers

Mısır

2021

Automated Design of Machine Learning and Search Algorithms

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An Evolutionary Algorithm Based Hyper-heuristic for the Set Packing Problem

Cited by 3 publications

References 16 publications

A 3D Offline Packing Algorithm considering Cargo Orientation and Stability

A 3D Offline Packing Algorithm considering Cargo Orientation and Stability

Solving the Set Packing Problem via a Maximum Weighted Independent Set Heuristic

Hyper-heuristics: Autonomous Problem Solvers

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