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

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

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

    101 Citations (Scopus)

    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.
    Original languageEnglish
    Pages (from-to)64-73
    JournalComputers and Operations Research
    Volume39
    Issue number1
    DOIs
    Publication statusPublished - Jan 2012

    Research Keywords

    • Heuristic
    • Knapsack packing problem
    • Simulated annealing algorithm

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