Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/86485
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Type: Journal article
Title: A hybrid evolutionary algorithm for wheat blending problem
Author: Li, X.
Bonyadi, M.
Michalewicz, Z.
Barone, L.
Citation: The Scientific World Journal, 2014; 2014:967254-1-967254-13
Publisher: Hindawi Publishing Corporation
Issue Date: 2014
ISSN: 1537-744X
1537-744X
Statement of
Responsibility: 
Xiang Li, Mohammad Reza Bonyadi, Zbigniew Michalewicz, and Luigi Barone
Abstract: This paper presents a hybrid evolutionary algorithm to deal with the wheat blending problem. The unique constraints of this problem make many existing algorithms fail: either they do not generate acceptable results or they are not able to complete optimization within the required time. The proposed algorithm starts with a filtering process that follows predefined rules to reduce the search space. Then the linear-relaxed version of the problem is solved using a standard linear programming algorithm. The result is used in conjunction with a solution generated by a heuristic method to generate an initial solution. After that, a hybrid of an evolutionary algorithm, a heuristic method, and a linear programming solver is used to improve the quality of the solution. A local search based posttuning method is also incorporated into the algorithm. The proposed algorithm has been tested on artificial test cases and also real data from past years. Results show that the algorithm is able to find quality results in all cases and outperforms the existing method in terms of both quality and speed.
Keywords: Triticum
Algorithms
Software
Food Quality
Rights: Copyright © 2014 Xiang Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1155/2014/967254
Grant ID: http://purl.org/au-research/grants/arc/DP0985723
http://purl.org/au-research/grants/arc/DP1096053
http://purl.org/au-research/grants/arc/DP130104395
Published version: http://dx.doi.org/10.1155/2014/967254
Appears in Collections:Aurora harvest 7
Computer Science publications

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