A novel shaking optimization algorithm for two-dimensional irregular strip-packing problem

This paper presents a new optimization algorithm titled “Shaking Optimization Algorithm” for the two-dimensional irregular strip packing problem. It is used to search the items sequence that gives shortest sheet length while the combined pixel-compaction algorithm is used to handle the pieces geometry and to place them onto the sheet building the layout with no overlaps. The Shaking Optimization Algorithm follows the common methodology of the Evolutionary Computations while utilizing different heuristics during the evolution process of the solution. It is a structured search algorithm that emulates the actual shaking process. It starts with reordering the items according to some criteria. While two heuristic-rules are to be applied to handle gaps that exist due to items sequence. The process of reordering and gap handling is to be repeated many times until some stopping criteria is met. The algorithm has been tested using five selected benchmark problems. The results show that the proposed algorithm outperforms many of the known evolutionary computation algorithms, while being a good competitor to some others. In particular, it gives a competitive solution in a very reasonable time compared with all other algorithms.