00000ctmaa22000003a 4500 UP-1685675941123923447 Buklod 20230927121423.0 aa rb |||1 u| ta 230927s2008 xx d |||| || | (iLib)UPTAC-00017783808 UPVTC rda eng LG 993.5 2008 C66 A74 Arellano, Jikky Ann P. author. EPGraph evolutionary programming for Graph Coloring Problem Jikky Ann P. Arellano [and] Augustianne Laurenne L. Barreta; John Paul T. Yusiong, adviser. 2008. [5], 53 leaves illustrations. Undergraduate thesis (B.S. Computer Science) -- University of the Philippines, Tacloban. Graph Theory, Graph Coloring Problem (GCP) is a problem of assigning colors used is dictated by some k-coloring. This coloring is known as the chromatic number of a graph. To compute for the upper bound of the chromatic number, the authors used a concept of Graph Theory which can be proven by Brook's Theorem. Several population-based algorithms such as Genetic Algorithm and Particle Swarm Optimization have already been used to solve the GCP. This study aims to solve the GCP using Evolutionary Programming, another population-based algorithm. Evolutionary Programming is similar to Genetic Algorithm except that Evolutionary Programming does not have any crossover operator. EP can successfully solve GCP and can find optimal solution with the right mutation operators and given enough time. Graph Theory. Graph Coloring Problem. Chromatic Number. Brook's Theorem. Genetic Algorithm. Particle Swarm Optimization. Evolutionary Programming. Barreta, Augustianne Laurenne L. author. Yusiong, John Paul T. adviser. FI UP UPTAC UPTAC LG 993.5 2008 C66 A74 Thesis