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Limited Re-Sequencing for Mixed-Models with Multiple Objectives, Part II: A Permutation Approach

Author(s): Patrick R. McMullen

Journal: American Journal of Operations Research
ISSN 2160-8830

Volume: 02;
Issue: 01;
Start page: 10;
Date: 2012;
Original page

Keywords: Permutation | Heuristic | Sequencing | Discrete Optimization

This research presents an approach to solving the limited re-sequencing problem for a JIT system when two objectives are considered for multiple processes. One objective is to minimize the number of setups; the other is to minimize the material usage rate [1]. For this research effort, each unique permutation of the problem’s demand structure is noted, and used as a mechanism for finding subsequent sequences. Two variants of this permutation approach are used: one employs a Monte-Carlo simulation, while the other employs a modification of Ant-Colony Optimization to find sequences satisfying the objectives of interest. Problem sets from the literature are used for assessment, and experimentation shows that the methodology presented here outperforms methodology from an earlier research effort [3].

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