H. Liao’s scientific contributions

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Publications (1)


Network optimization in supply chain: A KBGA approach
  • Article

January 2012

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99 Reads

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28 Citations

Decision Support Systems

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H. Liao

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In this paper, we present a Knowledge Based Genetic Algorithm (KBGA) for the network optimization of Supply Chain (SC). The proposed algorithm integrates the knowledge base for generating the initial population, selecting the individuals for reproduction and reproducing new individuals. From the literature, it has been seen that simple genetic-algorithm-based heuristics for this problem lead to and large number of generations. This paper extends the simple genetic algorithm (SGA) and proposes a new methodology to handle a complex variety of variables in a typical SC problem. To achieve this aim, three new genetic operators—knowledge based: initialization, selection, crossover, and mutation are introduced. The methodology developed here helps to improve the performance of classical GA by obtaining the results in fewer generations. To show the efficacy of the algorithm, KBGA also tested on the numerical example which is taken from the literature. It has also been tested on more complex problems.

Citations (1)


... They used two GA-based multipurpose metaheuristics to solve these problems. In [13], supply networks based on GA (in particular, knowledge-based genetic algorithm, KBGA) for optimization are provided. In [14], a multipurpose model of mixed integer programming for a closed loop network design was formulated. ...

Reference:

A model for optimizing plans for procurement of raw materials from regions of Russia in a timber-processing enterprise
Network optimization in supply chain: A KBGA approach
  • Citing Article
  • January 2012

Decision Support Systems