Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 39, Issue 15, Pages 12213-12219Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2012.04.055
Keywords
Random assignment problem; Synthesizing effect; Genetic algorithms; Markov chain
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Funding
- NSFC (National Natural Science Foundation of China) [71071049, 71132008]
- Natural Science Foundation of Hebei Province [F2011208056]
- Ministry of Education of China
- US National Science Foundation [1044845]
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Assignment problem is considered a well-known optimization problem in manufacturing and management processes in which a decision maker's point of view is merged into a decision process and a valid solution is established. In this study, taking the complementary relations between expected value and variance in decision making and the synthesizing effect of random variables into consideration, a new model for random assignment problems is proposed; in which the characteristic of assignment problems are considered to present a concrete scheme based on genetic algorithms (denoted by SE circle plus GA-SAF, for short). We study the model's convergence using the Markov chain theory, and analyze its performance through simulation. All of these indicate that this solution model can effectively aid decision making in the assignment process, and that it possesses the desirable features such as interpretability and computational efficiency, as such it can be widely used in many aspects including manufacturing, operations, logistics, etc. (C) 2012 Elsevier Ltd. All rights reserved.
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