The nonlinear complementarity model of industrial symbiosis network equilibrium problem
RAIRO - Operations Research - Recherche Opérationnelle, Volume 48 (2014) no. 4, pp. 559-594.

In this paper, we propose an industrial symbiosis network equilibrium model by using nonlinear complementarity theory. The industrial symbiosis network consists of industrial producers, industrial consumers, industrial decomposers and demand markets, which imitates natural ecosystem by means of exchanging by-products and recycling useful materials exacted from wastes. The industrial producers and industrial consumers are assumed to be concerned with maximization of economic profits as well as minimization of emissions. We describe the optimizing behavior, derive optimality conditions of the various decision-makers along with respective economic interpretations and establish the nonlinear complementarity model in accordance with the industrial symbiosis network equilibrium conditions. Based on the existence proof of the corresponding nonlinear complementarity model under reasonable assumptions, two groups of numerical examples are given to illustrate the rationality as well as the effectiveness of the model.

DOI: 10.1051/ro/2014024
Classification: 49J40, 90B06, 91A40
Keywords: industrial symbiotic networks, nonlinear complementarity, theory equilibrium conditions, multicriteria decision-making
     author = {Xu, Shiqin and Liu, Guoshan and Lv, Wendai and Liu, Yingmei},
     title = {The nonlinear complementarity model of industrial symbiosis network equilibrium problem},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {559--594},
     publisher = {EDP-Sciences},
     volume = {48},
     number = {4},
     year = {2014},
     doi = {10.1051/ro/2014024},
     mrnumber = {3264394},
     zbl = {1301.49028},
     language = {en},
     url = {}
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PB  - EDP-Sciences
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Xu, Shiqin; Liu, Guoshan; Lv, Wendai; Liu, Yingmei. The nonlinear complementarity model of industrial symbiosis network equilibrium problem. RAIRO - Operations Research - Recherche Opérationnelle, Volume 48 (2014) no. 4, pp. 559-594. doi : 10.1051/ro/2014024.

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