A Simulated Annealing Enhancement of the Best-Fit Heuristic for the Orthogonal Stock-Cutting Problem

Abstract

T he best-fit heuristic is a simple yet powerful one-pass approach for the two-dimensional rectangular stockcutting problem. It had achieved the best published results on a wide range of benchmark problems until the development of the approaches described in this paper. Here, we illustrate how improvements in solution quality can be achieved by the hybridisation of the best-fit heuristic together with simulated annealing and the bottom-left-fill algorithm. We compare and contrast the new hybrid approach with other approaches from the literature in terms of execution times and the quality of the solutions achieved. Using a range of standard benchmark problems from the literature, we demonstrate how the new approach achieves significantly better results than previously published methods on almost all of the problem instances. In addition, we provide results on 10 new benchmark problems to encourage further research and greater comparison between current and future methods.

A Hybrid Algorithm for Strip Packing Problem with Rotation Constraint

“…Meanwhile, BF+GA, BF+SA and BF+TS in [16], HRP [20], FH [30] and DHA [29] are introduced for comparison. The results of BF+GA, BF+SA and BF+TS are from [16], the results of HRP and FH are from [30], and the results of DHA are from [29]. In tables, "op" represents the optimal height, OPTMA# denotes the number of the optimal height obtained by different algorithms.…”

Bidirectional best-fit heuristic considering compound placement for two dimensional orthogonal rectangular strip packing

“…Bortfeldt (2006) implemented a GA (SPGAL) which operates directly on a search space of complete packing, rather than on an encoding of orderings such as those of Jakobs (1996) and Liu & Teng (1999). Burke et al (2009) enhanced the the BF heuristic (Burke et al, 2004) with the hybrid simulated 3…”

“…The techniques from the literature are: Best-fit (BF) (Burke et al, 2004), Best-fit with simulated annealing (BF-SA) (Burke et al, 2009), squeaky wheel optimisation (SWP) (Burke et al, 2011), SVC(SubKP) (Belov et al, 2008), GRASP (Alvarez-Valdes et al, 2009), an 'intelligent search algorithm' (ISA) (Leung et al, 2011) and iterative doubling binary search (IDBS) (Wei et al, 2011). In the case that an approach is stochastic, the average performance reported is used to calculate %-gap to compare to our deterministic method.…”

A Reinforced Tabu Search Approach for 2D Strip Packing

“…Note that many (usually greedy) selection / placement heuristics have been investigated according to various criteria (Alvarez-Valdes et al, 2008, 2007Aşik & Özcan, 2009;Burke et al, 2009). …”