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The IUP Journal of Computer Sciences :
Graph Coloring with Memetic Algorithm
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Design and analysis of new algorithms are ongoing phenomena in the field of computer science. NP problems are attracting designers to design both heuristic and approximate algorithms that can result in optimal and time-space efficient algorithms. This paper aims at designing a memetic algorithm (also known as metaheuristic or hybrid heuristic), for optimal vertex coloring of a simple, symmetric and connected graph. Besides its various uses, the problem has the essence of efficient algorithm design in large-scale test graphs. The earlier works, though encouraging, could not draw a conclusion that is deterministic. This paper provides further information on the subject.

 
 
 

Proper coloring of a simple, symmetric and connected graph is a classical problem that deals with m-colorability optimization problem. The problem asks for the smallest integer m, for which the graph G = (V, E) with vertex set V and edge set E can be colored properly. This minimum integer is called the chromatic number X(G). A k-vertex coloring of any graph G is an assignment of k-colors 1,2,3,..., k to the vertices of G.

The reasons for the importance of the graph coloring problem are twofold. First, there are several areas of practical interest in which the ability to color an undirected graph with the smallest number of colors has direct influence on how efficiently a certain target problem can be solved. Such areas include timetable scheduling (Wood, 1969), examination scheduling (Leighton, 1979), register allocation (Chow and Hennessy, 1984), printed circuit testing (Garey et al., 1976), electronic bandwidth allocation (Gamst, 1986), microcode optimization (Micheli, 1994), channel routing (Sarma et al., 1985), the design and operation of flexible manufacturing systems (Stecke, 1985), computation of sparse Jacobian elements by finite differencing in mathematical programming (Coleman and More, 1983), etc.

The other reason is: the graph coloring problem has been shown to be computationally hard at a variety of levels - not only its decision problem variant is NP-complete (Garey and Johnson, 1979), but also its approximate version is NP-hard (Baase and Gelder, 1999).

 
 
 

Graph Coloring, Memetic Algorithm, Flexible manufacturing systems, Genetic Algorithms, Sequential Algorithm Graph Coloring Problem, Memetic Graph Coloring Problem, Neural Networks Algorithms, Operational Research, Optimization by Simulated Annealing.