TERASHIMA2 data set Description: 480 Irregular test instances Artificially created data set with convex and non-convex polygons. Procedure described by López-Camacho, 2012. In each instance name, the number after letter C is the number of non-convex pieces. Example: Instance TA001C5.txt has 5 non-convex pieces. (Except in instances TU***C*C*.txt and TX***C*C*.txt, in which the number of non-convex pieces may vary). For each instance we report: - first line: the number N of pieces; - second line: the width and height of the rectangular objects where pieces are placed. - each of next N lines: number of vertices and coordinates x1 y1 x2 y2 x3 y3 ... xN yN. Coordinates are counterclockwise. Optimum is known and it is given. Optimum placing for .txt is in file Op.txt For each file Op.txt we report: - first line: the number of objects followed by how many pieces are in each object. - second line: the width and height of the rectangular objects where pieces are placed. - each of next N lines: number of vertices and coordinates x1 y1 x2 y2 x3 y3 ... xN yN where each piece is placed in the optimal solution. Reference: López-Camacho, E. An Evolutionary Framework for Producing Hyper-heuristics for Solving the 2D Irregular Bin Packing Problem PhD Dissertation. Tecnológico de Monterrey, 2012. Some articles that have solved this data set: López-Camacho, E., Terashima-Marín, H. and Conant-Pablos, S. E. The impact of the bin packing problem structure in hyper-heuristic performance. In GECCO'12: Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation (2012), ACM New York, NY, USA, pp. 1545-1546. DOI=10.1145/2330784.2331040 López-Camacho, E., Terashima-Marín, H. and Ross, P. A hyper-heuristic for solving one and two-dimensional bin packing problems. In GECCO '11: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation (2011), Natalio Krasnogor (Ed.), ACM, New York, NY, USA, pp. 257-258. DOI=10.1145/2001858.2002003