Multi-objective optimization for resource network synthesis in eco-industrial parks using an integrated analytic hierarchy process

• Main Authors: Leong, Yik T., Lee, Jui Yuan, Tan, Raymond Girard R., Foo, Ji Jinn, Chew, Irene Mei Leng
• Format: text
• Published: Animo Repository 2017
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/785; https://animorepository.dlsu.edu.ph/context/faculty_research/article/1784/type/native/viewcontent
• Institution: De La Salle University

© 2016 Elsevier Ltd The establishment of eco-industrial parks (EIPs) is an effective approach to developing industrial symbiosis in which plants of different entities could reduce waste production through co-sharing common utilities and/or resources, thus minimizing environmental impacts. Common resources such as heat and water are often the precursor of forming the symbiotic resource exchange network in an EIP. However, synthesizing the resource network in an EIP is a complex decision-making process involving the optimization of various design criteria by a group of decision-makers with different interests. Hence, this paper presents a multi-objective optimization approach that uses numerical representation to rank the preferences of each participating plant on the predefined criteria for building an EIP. The analytic hierarchy process (AHP) is a well-established decision-making technique for the analysis of complex decision problems. With its mathematical simplicity and flexibility, AHP can be integrated with different optimization techniques, such as mathematical programming. In this work, we develop an integrated AHP (IAHP) approach to the formation of an optimum resource network in an EIP. The optimization model is formulated to obtain a balanced solution that achieves the optimum design criteria defined by a given set of constraints. The design criteria considered in this work include economic performance, environmental impact, connectivity and network reliability. A case study on the synthesis of a chilled and cooling water network is used to illustrate the proposed methodology.