scholarly journals An improved hybrid ant-local search algorithm for the partition graph coloring problem

2016 ◽  
Vol 293 ◽  
pp. 55-61 ◽  
Author(s):  
Stefka Fidanova ◽  
Petrică Pop
Keyword(s):  
Local Search ◽  
Graph Coloring ◽  
Search Algorithm ◽  
Local Search Algorithm ◽  
Coloring Problem ◽  
Graph Coloring Problem ◽  
Partition Graph

scholarly journals Reduction and Local Search for Weighted Graph Coloring Problem

2020 ◽  
Vol 34 (03) ◽  
pp. 2433-2441 ◽  
Author(s):  
Yiyuan Wang ◽  
Shaowei Cai ◽  
Shiwei Pan ◽  
Ximing Li ◽  
Monghao Yin
Keyword(s):  
Local Search ◽  
Graph Coloring ◽  
Search Algorithm ◽  
Weighted Graph ◽  
Coloring Problem ◽  
Massive Graphs ◽  
Configuration Checking ◽  
New Variant ◽  
Graph Coloring Problem ◽  
Important Extension

The weighted graph coloring problem (WGCP) is an important extension of the graph coloring problem (GCP) with wide applications. Compared to GCP, where numerous methods have been developed and even massive graphs with millions of vertices can be solved well, fewer works have been done for WGCP, and no solution is available for solving WGCP for massive graphs. This paper explores techniques for solving WGCP, including a lower bound and a reduction rule based on clique sampling, and a local search algorithm based on two selection rules and a new variant of configuration checking. This results in our algorithm RedLS (Reduction plus Local Search). Experiments are conducted to compare RedLS with the state-of-the-art algorithms on massive graphs as well as conventional benchmarks studied in previous works. RedLS exhibits very good performance and robustness. It significantly outperforms previous algorithms on all benchmarks.

A Modified Binary Crow Search Algorithm for Solving the Graph Coloring Problem

2020 ◽  
Vol 11 (2) ◽  
pp. 28-46 ◽  
Author(s):  
Yassine Meraihi ◽  
Mohammed Mahseur ◽  
Dalila Acheli
Keyword(s):  
Graph Coloring ◽  
Optimization Problem ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Distribution Method ◽  
Local Optima ◽  
Coloring Problem ◽  
Graph Coloring Problem ◽  
Np Hard Problem ◽  
The Right

The graph coloring problem (GCP) is a well-known classical combinatorial optimization problem in graph theory. It is known to be an NP-Hard problem, so many heuristic algorithms have been employed to solve this problem. This article proposes a modified binary crow search algorithm (MBCSA) to solve the graph coloring problem. First, the binary crow search algorithm is obtained from the original crow search algorithm using the V-shaped transfer function and the discretization method. Second, we use chaotic maps to choose the right values of the flight length (FL) and the awareness probability (AP). Third, we adopt the Gaussian distribution method to replace the random variables used for updating the position of the crows. The aim of these contributions is to avoid the premature convergence to local optima and ensure the diversity of the solutions. To evaluate the performance of our algorithm, we use the well-known DIMACS benchmark graph coloring instances. The simulation results reveal the efficiency of our proposed algorithm in comparison with other existing algorithms in the literature.

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