Fuzzy mixed integer non-linear programming model for the design of an algae-based eco-industrial park with prospective selection of support tenants under product price variability
Eco-industrial parks provide a platform for the application of industrial symbiosis where the synergistic network of companies reuse portions of their by-products to reduce disposed waste, reduce environmental emissions, and improve plant efficiency. However, designing a complex network of material...
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| Vydané v: | Journal of cleaner production Ročník 136; s. 183 - 196 |
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| Hlavní autori: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Elsevier Ltd
10.11.2016
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| ISSN: | 0959-6526, 1879-1786 |
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| Abstract | Eco-industrial parks provide a platform for the application of industrial symbiosis where the synergistic network of companies reuse portions of their by-products to reduce disposed waste, reduce environmental emissions, and improve plant efficiency. However, designing a complex network of material and energy exchanges between companies in an industrial park while satisfying multiple conflicting objectives require a systematic design methodology. In addition, strategic decision-making in an eco-industrial park involves the selection of prospective companies (i.e., support tenants), which complement the existing companies (i.e., anchor tenants). In this study, a fuzzy mixed-integer non-linear programming model is proposed to select prospective support tenants in an eco-industrial park while satisfying the product demand, minimizing the environmental footprint of the eco-industrial park, and also maximizing the annualized profit of each company in the eco-industrial park. A hypothetical but realistic case study involving an algae-based eco-industrial park is used to demonstrate the application of the model. The results demonstrate the selection of the appropriate support tenants for the algae-based eco-industrial park together with the optimal plant configuration. Sensitivity analysis is used to assess the performance of the algae-based eco-industrial park with respect to the changes in prices of the by-products. The developed model thus aid the planners of an eco-industrial park in assessing which among the prospective support tenants would best complements an existing anchor tenant. Furthermore, the model can also identify price negotiation points between tenants for some product streams which may show sensitivity on the plant capacity of each tenant. |
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| AbstractList | Eco-industrial parks provide a platform for the application of industrial symbiosis where the synergistic network of companies reuse portions of their by-products to reduce disposed waste, reduce environmental emissions, and improve plant efficiency. However, designing a complex network of material and energy exchanges between companies in an industrial park while satisfying multiple conflicting objectives require a systematic design methodology. In addition, strategic decision-making in an eco-industrial park involves the selection of prospective companies (i.e., support tenants), which complement the existing companies (i.e., anchor tenants). In this study, a fuzzy mixed-integer non-linear programming model is proposed to select prospective support tenants in an eco-industrial park while satisfying the product demand, minimizing the environmental footprint of the eco-industrial park, and also maximizing the annualized profit of each company in the eco-industrial park. A hypothetical but realistic case study involving an algae-based eco-industrial park is used to demonstrate the application of the model. The results demonstrate the selection of the appropriate support tenants for the algae-based eco-industrial park together with the optimal plant configuration. Sensitivity analysis is used to assess the performance of the algae-based eco-industrial park with respect to the changes in prices of the by-products. The developed model thus aid the planners of an eco-industrial park in assessing which among the prospective support tenants would best complements an existing anchor tenant. Furthermore, the model can also identify price negotiation points between tenants for some product streams which may show sensitivity on the plant capacity of each tenant. |
| Author | Aviso, Kathleen B. Culaba, Alvin B. El-Halwagi, Mahmoud M. Cuello, Joel L. Ubando, Aristotle T. Ng, Denny K.S. Tan, Raymond R. |
| Author_xml | – sequence: 1 givenname: Aristotle T. orcidid: 0000-0001-5471-5421 surname: Ubando fullname: Ubando, Aristotle T. email: aristotle.ubando@dlsu.edu.ph organization: Mechanical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines – sequence: 2 givenname: Alvin B. surname: Culaba fullname: Culaba, Alvin B. organization: Mechanical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines – sequence: 3 givenname: Kathleen B. surname: Aviso fullname: Aviso, Kathleen B. organization: Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines – sequence: 4 givenname: Raymond R. surname: Tan fullname: Tan, Raymond R. organization: Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines – sequence: 5 givenname: Joel L. surname: Cuello fullname: Cuello, Joel L. organization: Agricultural and Biosystems Engineering Department, The University of Arizona, Tucson, AZ, USA – sequence: 6 givenname: Denny K.S. surname: Ng fullname: Ng, Denny K.S. organization: Department of Chemical and Environmental Engineering/Centre of Excellence for Green Technologies, The University of Nottingham, Malaysia Campus, Semenyih, Malaysia – sequence: 7 givenname: Mahmoud M. surname: El-Halwagi fullname: El-Halwagi, Mahmoud M. organization: Chemical Engineering Department, Texas A&M University, College Station, TX 77843, USA |
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| Keywords | Fuzzy set theory Microalgae Bioenergy Eco-industrial parks Mixed-integer non-linear programming |
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| Title | Fuzzy mixed integer non-linear programming model for the design of an algae-based eco-industrial park with prospective selection of support tenants under product price variability |
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