An Evolutionary Algorithm for Weighted Graph Coloring Problem

Sungu, Gizem; Boz, Betul

doi:10.1145/2739482.2768488

Cited by 3 publications

(6 citation statements)

References 10 publications

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“…In our initial work, Pool Based Evolutionary Algorithm (PBEA) [47], we have proposed a primitive pool to store unassigned vertices. Even if some vertices in the pool can be placed to color classes of the offspring already generated in the previous iterations, no intelligent mechanism was proposed to detect them.…”

Section: Algorithm 3: Search Back Operationmentioning

confidence: 99%

“…output of our integrated crossover operator (InCX) and three outputs of crossover operators presented in the literature are given in Fig. 3, which are Conflict-free Partition Crossover (CFPX) [44], Cost-oriented Crossover (COPX) [45], Pool Based Crossover (PBC) [47]. The offsprings generated by CFPX, COPX and PBC still have uncolored vertices.…”

Section: Algorithm 3: Search Back Operationmentioning

confidence: 99%

“…In this section, the performance of the proposed work is compared with HEA [44], COMA [45] and our initial work PBEA [47] using randomly generated graphs and the graphs derived from DIMACS benchmarks. For each graph, the total cost, the number of uncolored vertices and the execution time of the algorithms are the main comparison metrics.…”

Section: Experimental Studymentioning

confidence: 99%

“…To evaluate the performance of the operators in our algorithm, the proposed work is compared with our initial study PBEA [47] using three graphs where n=500 and α={0.25, 0.60, 0.90}. The performance of the algorithms are measured with or without using their local search techniques.…”

Section: Experimental Studymentioning

confidence: 99%

“…Preliminary work of this research [47] was presented at the Genetic and Evolutionary Computation Conference (GECCO'15), Madrid, Spain, 2015.…”

Section: Acknowledgmentmentioning

confidence: 99%

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Integrated Crossover Based Evolutionary Algorithm for Coloring Vertex-Weighted Graphs

Boz

Sungu

2020

IEEE Access

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Graph coloring is one of the main optimization problems widely studied in the literature. In this study, we propose a novel evolutionary algorithm called Integrated Crossover Based Evolutionary Algorithm with its unique crossover operator and local search technique for coloring vertex-weighted graphs. The integrated crossover operator targets to use the domain-specific information in the individuals and the local search technique aims to explore neighborhood solutions using weighted-swap operations. The performance of the proposed work is evaluated on synthetic benchmarks and DIMACS instances by comparing it with leading evolutionary algorithms from the literature. The experimental study indicates that our algorithm outperforms the related work in 71% of the test cases and achieves the same result in 17% of the test cases provided in the synthetic benchmarks. The experiments performed on DIMACS benchmarks denote that our algorithm finds the best number of colors in 70 out of 73 graphs, so the proposed work is very successful in coloring vertex-weighted graphs within a reasonable amount of time.

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Section: Algorithm 3: Search Back Operationmentioning

confidence: 99%

Section: Algorithm 3: Search Back Operationmentioning

confidence: 99%

Section: Experimental Studymentioning

confidence: 99%

Section: Experimental Studymentioning

confidence: 99%

“…Preliminary work of this research [47] was presented at the Genetic and Evolutionary Computation Conference (GECCO'15), Madrid, Spain, 2015.…”

Section: Acknowledgmentmentioning

confidence: 99%

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Integrated Crossover Based Evolutionary Algorithm for Coloring Vertex-Weighted Graphs

Boz

Sungu

2020

IEEE Access

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Solving Dynamic Graph Coloring Problem Using Dynamic Pool Based Evolutionary Algorithm

Sungu

Boz

2017

Applications of Evolutionary Computation

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Pool-based Evolutionary Algorithm for the Bin Packing Problem

Boz

Yıldız

2021

International Journal of Advances in Engineering and Pure Sciences

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Bin packing problem is one of the most important optimization problems from the literature. In this work, we propose a novel pool-based evolutionary algorithm for solving the one-dimensional bin packing problem. The algorithm exploits a pool-based crossover operator that aims to increase the search space of the problem and combine and remap as a local search technique that aims to improve the quality of the solution by considering underutilized bins in the offspring. The proposed method is applied to medium and hard instances taken from benchmark problem sets and is compared with six algorithms from the literature. Our experimental evolution indicates that the proposed algorithm outperforms these algorithms in most of the test cases provided.

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An Evolutionary Algorithm for Weighted Graph Coloring Problem

Cited by 3 publications

References 10 publications

Integrated Crossover Based Evolutionary Algorithm for Coloring Vertex-Weighted Graphs

Integrated Crossover Based Evolutionary Algorithm for Coloring Vertex-Weighted Graphs

Solving Dynamic Graph Coloring Problem Using Dynamic Pool Based Evolutionary Algorithm

Pool-based Evolutionary Algorithm for the Bin Packing Problem

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