An empirical investigation of meta-heuristic and heuristic algorithms for a 2D packing problem |
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| Institution: | 1. Key Laboratory of Computer Integrated Manufacturing System, School of Electromechanical Engineering, Guangdong University of Technology, 510006, China;2. School of Business Administration, South China University of Technology, 510640 Guangzhou, China;3. Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore;4. International Center of Management Science and Engineering, School of Management and Engineering, Nanjing University, Nanjing, 210093, China;1. School of Information Technology, Deakin University, Geelong 3216, Australia;2. Department of Statistics and Operations Research, College of Science, Kuwait University, P.O. Box 5969, Safat 13060, Kuwait;1. Southampton Business School, University of Southampton, UK;2. Department of Statistics and Operations Research, University of Valencia, Doctor Moliner 50, Burjassot 46100, Spain;3. Grupo de Sistemas de Optimización Aplicada, Instituto Tecnológico de Informática, Ciudad Politécnica de la Innovación, Edificio 8G, Acc. B., Universitat Politècnica de València, Camino de Vera s/n, València 46021, Spain |
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| Abstract: | In this paper we consider the two-dimensional (2D) rectangular packing problem, where a fixed set of items have to be allocated on a single object. Two heuristics, which belong to the class of packing procedures that preserve bottom-left (BL) stability, are hybridised with three meta-heuristic algorithms (genetic algorithms (GA), simulated annealing (SA), naı̈ve evolution (NE)) and local search heuristic (hill-climbing). This study compares the hybrid algorithms in terms of solution quality and computation time on a number of packing problems of different size. In order to show the effectiveness of the design of the different algorithms, their performance is compared to random search (RS) and heuristic packing routines. |
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