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Utility network optimization in eco-industrial parks by a multi-leader follower game methodology
Manuel A. Ramos, Mariona Rocafull, Marianne Boix, Didier Aussel, Ludovic Montastruc, Serge Domenech

Utility network optimization in eco-industrial parks by a multi-leader follower game methodology

Science & Mathematics Published 2018 Verification Pending

Overview & Synopsis

A multi-leader-follower game (MLFG) model for the design of the utility network in an eco-industrial park (EIP) is studied and implemented by introducing the concept of an environmental authority. The methodology also considers the flowsheet simulation of each enterprise involved in the EIP in order to obtain utility consumption of each enterprise operating by itself. The approach is validated on a case study of a potential Norwegian EIP. In the latter, multi-leader-single-follower and single-leader-multi-follower game models are studied. Each enterprise's objective is to minimize the total annualized cost, while the EIP authority objective is to minimize the equivalent CO2 consumption related to utility consumption within the ecopark. The MLFG is transformed into a MOPEC and solved using GAMS® as an NLP. The methodology proposed is proven to be reliable in multi-criteria scenarios compared to traditional multiobjective optimization approaches, providing numerical Nash/Stackelberg equilibrium solutions and specifically in EIP planning and optimization.

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Document Information

Document Title Utility network optimization in eco-industrial parks by a multi-leader follower game methodology
Author / Organization Manuel A. Ramos, Mariona Rocafull, Marianne Boix, Didier Aussel, Ludovic Montastruc, Serge Domenech
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2018
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-104239
Original Source Link Visit Source Page on hal.science »