A hybrid simulated annealing metaheuristic algorithm for the two-dimensional knapsack packing problem

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

95 Scopus Citations
View graph of relations

Author(s)

  • Stephen C.H. Leung
  • Defu Zhang
  • Changle Zhou
  • Tao Wu

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)64-73
Journal / PublicationComputers and Operations Research
Volume39
Issue number1
Publication statusPublished - Jan 2012

Abstract

The rectangle knapsack packing problem is to pack a number of rectangles into a larger stock sheet such that the total value of packed rectangles is maximized. The paper first presents a fitness strategy, which is used to determine which rectangle is to be first packed into a given position. Based on this fitness strategy, a constructive heuristic algorithm is developed to generate a solution, i.e. a given sequence of rectangles for packing. Then, a greedy strategy is used to search a better solution. At last, a simulated annealing algorithm is introduced to jump out of the local optimal trap of the greedy strategy, to find a further improved solution. Computational results on 221 rectangular packing instances show that the presented algorithm outperforms some previous algorithms on average. © 2011 Elsevier Ltd. All rights reserved.

Research Area(s)

  • Heuristic, Knapsack packing problem, Simulated annealing algorithm

Citation Format(s)

A hybrid simulated annealing metaheuristic algorithm for the two-dimensional knapsack packing problem. / Leung, Stephen C.H.; Zhang, Defu; Zhou, Changle et al.
In: Computers and Operations Research, Vol. 39, No. 1, 01.2012, p. 64-73.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review