Recent developments in evolutionary computation for manufacturing optimisation: problems, solutions and comparisons

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@Article{chrams00,

• author = "Christos Dimopoulos and Ali M. S. Zalzala",
• title = "Recent developments in evolutionary computation for manufacturing optimisation: problems, solutions and comparisons",
• journal = "IEEE Transactions on Evolutionary Computation",
• year = "2000",
• volume = "4",
• number = "2",
• pages = "93--113",
• month = jul,
• email = "chris_dimop@hotmail.com",
• keywords = "genetic algorithms, genetic programming, evolutionary computation, manufacturing optimization, assembly line balancing, combinatorial NP-hard problems, evolutionary computation, flow shop scheduling, intelligent techniques, job shop scheduling, manufacturing optimisation, process planning, artificial intelligence, computational complexity, evolutionary computation, production control",
• ISSN = "1089-778X",
• DOI = "doi:10.1109/4235.850651",
• size = "21 pages",
• abstract = "The use of intelligent techniques in the manufacturing field has been growing the last decades due to the fact that most of manufacturing optimisation problems are combinatorial and NP hard. This report examines recent developments in the field of evolutionary computation for manufacturing optimisation. Significant papers in various areas are highlighted and comparisons of results are given wherever data is available. A wide range of problems is covered, from job shop and flow shop scheduling, to process planning and assembly line balancing",
• notes = "Also known as \cite{850651}",

}

Genetic Programming entries for Christos Dimopoulos Ali M S Zalzala

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