Solving packing problems by a distributed global optimization algorithm

Nian Ze Hu, Han-Lin Li, Jung Fa Tsai*

*Corresponding author for this work

Research output: Contribution to journalArticle

4 Scopus citations

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.

Original languageEnglish
Article number931092
JournalMathematical Problems in Engineering
Volume2012
DOIs
StatePublished - 17 Aug 2012

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