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Dynamic multiobjective optimization of large‐scale industrial production systems: An emerging strategy
Author(s) -
Benali M.,
Hammache A.,
Aubé F.,
Dipama J.,
Cantave R.
Publication year - 2007
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.1329
Subject(s) - multi objective optimization , production (economics) , context (archaeology) , computer science , scale (ratio) , mathematical optimization , raw material , industrial engineering , biochemical engineering , operations research , process engineering , engineering , economics , mathematics , ecology , physics , quantum mechanics , paleontology , biology , macroeconomics
The large industrial production systems face several conflicting challenges of energy efficiency improvements, lower consumption of raw materials per unit of production, extending the product durability, minimizing the environmental impacts, and cautious use of natural resources. In this context it is well obvious that the optimization problem is multiobjective in nature. The paper emphasizes critical review of optimization methods of large‐scale industrial production systems and presentation of a novel systematic multiobjective and multiscale optimization methodology based mainly on a combined local optimality search with global optima determination, and advanced system decomposition and constraint handling. © Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources, 2007.