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Erschienen in:
2013 | OriginalPaper | Buchkapitel
A Heuristic to the Multiple Container Loading Problem with Preference
verfasst von : Tian Tian, Andrew Lim, Wenbin Zhu
Erschienen in: Contemporary Challenges and Solutions in Applied Artificial Intelligence
Verlag: Springer International Publishing
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In this paper, we address the Multiple Container Loading Problem with Preference (MCLPP). It is derived from the real problems proposed by an audio equipment manufacturer. In the MCLPP, the numbers of various types of boxes can be adjusted based on box preferences.We need to add or delete boxes in a restricted way so that the ratio of the total preference of boxes to the total cost of containers is maximized.We develop a three-step search scheme to solve this problem. Test data is modified from existing benchmark test data for the multiple container loading cost minimization problem. Computational experiments show our approach is able to provide high quality solutions and they satisfy the need of the manufacturer.
