Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/43889
Title: Intelligent optimization algorithms : a stochastic closed-loop supply chain network problem involving oligopolistic competition for multiproducts and their product flow routings
Authors: Zhou, Y
Chan, CK 
Wong, KH
Lee, YCE
Issue Date: 2015
Publisher: Hindawi Publishing Corporation
Source: Mathematical problems in engineering, 2015, v. 2015, 918705 How to cite?
Journal: Mathematical problems in engineering 
Abstract: Recently, the first oligopolistic competition model of the closed-loop supply chain network involving uncertain demand and return has been established. This model belongs to the context of oligopolistic firms that compete noncooperatively in a Cournot-Nash framework. In this paper, we modify the above model in two different directions. (i) For each returned product from demand market to firm in the reverse logistics, we calculate the percentage of its optimal product flows in each individual path connecting the demand market to the firm. This modification provides the optimal product flow routings for each product in the supply chain and increases the optimal profit of each firm at the Cournot-Nash equilibrium. (ii) Our model extends the method of finding the Cournot-Nash equilibrium involving smooth objective functions to problems involving nondifferentiable objective functions. This modification caters for more real-life applications as a lot of supply chain problems involve nonsmooth functions. Existence of the Cournot-Nash equilibrium is established without the assumption of differentiability of the given functions. Intelligent algorithms, such as the particle swarm optimization algorithm and the genetic algorithm, are applied to find the Cournot-Nash equilibrium for such nonsmooth problems. Numerical examples are solved to illustrate the efficiency of these algorithms.
URI: http://hdl.handle.net/10397/43889
ISSN: 1024-123X
EISSN: 1563-5147
DOI: 10.1155/2015/918705
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