5 th International & 26 th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014) December 12 th –14 th , 2014, IIT Guwahati, Assam, India 157-1 Implementating the Genetic Algorithm with VLSI Approach for Optimization of Sheet Metal Nesting K.Ramesh 1* , N.Baskar 2 *1 Department of Mechanical Engineering, M.I.E.T Engineering College, Tiruchirappalli, Tamil Nadu - 620 007, India. 2 Department of Mechanical Engineeering, M.A.M College of Engineering, Tiruchirappalli, Tamil Nadu-621 105, India. Abstract As Engineering becomes more advanced and the business in the industrial world becomes more competitive, hence optimization technique becomes an essential part of an any industry or organization. The objective of this paper is to minimize the material wastage by the optimum layout of two-dimensional work piece within constraints imposed by stock size and material. This approach deals with how it can be effectively utilized in the sheet metal industry to have the best arrangement of irregular shaped parts in the sheet. This can be possible by using genetic algorithm (GA) approach which provides a best sequence of parts with their orientation and also deals with how the parts can be effectively utilized in sheet metal. This analysis mainly depends on the cutting process, size and shape of the sheet for different combination of parts and subsequent operations required on the part. This heuristic based genetic algorithm generates optimum layout considering factors such as minimum material wastage with their orientation by eliminating human efforts. Keywords: Genetic Algorithm, initial population, cross over, mutation, strip 1. Introduction The nesting of two-dimensional shapes for press tool design is general optimization problem. In mass production industries, small inefficiencies will lead to very large material wastage. This is also known as two-dimensional cutting stock problem. This problem is commonly encountered in industries such as lock, Sheet metal, aerospace, shipbuilding, clothes and shoe manufacturing. The problem was solved by using mathematical technique in the earlier stage. The irregular parts are considered as orthogonal line features. Arrangements of parts on a sheet depends on the sequence which the parts with their orientation. In order to generate an optimum arranged pattern, it is essential parts in proper sequence and their orientations. The complete procedure considers all possible combinations of part sequence and their orientation to give out the optimum nested pattern. But it takes considerably longer time to achieve the optimum solution. Such a computational complexity can be overcome with genetic algorithm. Once the sequence and orientations of parts are selected randomly, parts are to be arranged on the sheet in acceptable positions. The acceptable position of the part is the one where the part neither overlaps with other neither nested parts nor crosses the boundary of the strip. It is necessary to find out the position of the part, with other the over lapping parts that are nested already. Hence this technique is employed in which the center of all parts which lies in the same line and quickly identify the position the part with respect to the strip. Antonio Albano and Giusseppe Sapuppo developed an automatic approach, which transforms the allocation problem into a search process through a “space” of candidate solution. Since this space is very large, heuristic algorithm will be employed for shortening the search. This search indicates the optimal arrangement of irregular parts into a rectangular resource. The problem had been to a search of an optimal path in a graph, and an algorithm had been implanted which provides an approximate solution with less process time. A.Y.Nee, V.C.Venkatesh developed a heuristic algorithm for the layout of metal stamping blanks with computer user friendly dialogue. The algorithm creates an optimum layout considering factors such