A new metaheuristic genetic-based placement algorithm for 2D strip packing

• Published in: Journal of industrial engineering international Vol. 10; no. 1; pp. 1 - 16
• Main Authors: Thomas, Jaya, Chaudhari, Narendra S
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer 01.04.2014; Springer Berlin Heidelberg; Islamic Azad University, South Tehran Branch
• Subjects: Combinatorial optimization; Crossover; Engineering; Engineering Economics; Facility Management; Fitness; Genetic algorithm; Industrial and Production Engineering; Logistics; Marketing; Mathematical and Computational Engineering; Operation research; Organization; Original Research; Placement approach; Quality Control; Reliability; Safety and Risk; Strip packing; Genetic algorithm; Combinatorial optimization; Crossover; Operation research; Placement approach; Strip packing; Fitness
• ISSN: 2251-712X; 1735-5702; 2251-712X
• DOI: 10.1007/s40092-014-0047-9

Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The problem is a complex NP-hard combinatorial optimization, thus a heuristic based on genetic algorithm is proposed to solve it. In this paper, we give a hybrid approach which combined genetic encoding and evolution scheme with the proposed placement approach. Such a combination resulted in better population evolution and faster solution convergence to optimal. The approach is subjected to a comprehensive test using benchmark instances. The computation results validate the solution and the effectiveness of the approach.