APPLICATION OF GROUP GENETIC ALGORITHM FOR GENERATION OF CELLS TO SOLVE A MACHINE LAYOUT PROBLEM - Nyakudya, Ratidzo Yvonne; Kapisauro, Andrew; Muvunzi, Rumbidzai; Mpofu, Khumbulani (European Scientific Journal, ESJ, 2015)
This paper explains the improvement of a layout arrangement as a result of application of Group Genetic Algorithm (GGA) on an excel platform for generaation of cells, in celluar manufacturing to minimize distance travelled and materials handling between workstations. It is based on a case study of ABC (Pvt) Ltd, a privately owned manufacturing company in Zimbabwe. The main objective of the study is to come up with manufacturing cells of machine part matrix generated from chromosomes using GGA. The researchers use the GGA to come up with a machine part matrix which reduces distances between machines which processes related parts. Excel is used in calculating fitness function values and the analysis of the best chromosome is done using the radar and line plots. From the study the first offspring in the second generation (chrom 4) is chosen as the best chromosome which enables best machine layout with 83% machine-part movement minimization and 62% machine utilization and 73% effectiveness.