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Solving Packing Problems by a Distributed Global Optimization Algorithm

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  • Nian-Ze Hu
  • Han-Lin Li
  • Jung-Fa Tsai

Abstract

Packing optimization problems aim to seek the best way of placing a given set of rectangular boxes within a minimum volume rectangular box. Current packing optimization methods either find it difficult to obtain an optimal solution or require too many extra 0-1 variables in the solution process. This study develops a novel method to convert the nonlinear objective function in a packing program into an increasing function with single variable and two fixed parameters. The original packing program then becomes a linear program promising to obtain a global optimum. Such a linear program is decomposed into several subproblems by specifying various parameter values, which is solvable simultaneously by a distributed computation algorithm. A reference solution obtained by applying a genetic algorithm is used as an upper bound of the optimal solution, used to reduce the entire search region.

Suggested Citation

  • Nian-Ze Hu & Han-Lin Li & Jung-Fa Tsai, 2012. "Solving Packing Problems by a Distributed Global Optimization Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-13, July.
    • Handle: RePEc:hin:jnlmpe:931092
    DOI: 10.1155/2012/931092
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