A hybrid approach based on the genetic algorithm and neural network to design an incremental cellular manufacturing system

Applied Soft Computing Journal

Volumn 11, Issue 6, 2011, Pages 4195-4202

  Rezaeian, J ^a   Javadian, N ^a   Tavakkoli Moghaddam, R ^b   Jolai, F ^b  

^a DEPARTMENT OF INDUSTRIAL ENGINEERING   (Iran)

^b UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Cellular manufacturing system; Evolutionary algorithms; Genetic algorithm; Incremental cell formation; Neural network

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CELLULAR MANUFACTURING SYSTEMS; COMPUTATIONAL ANALYSIS; DYNAMIC ENVIRONMENTS; HYBRID APPROACH; INCREMENTAL CELL FORMATION; JOB SHOP; NONLINEAR PROGRAMMING MODEL; OPTIMAL SOLUTIONS;

COMPUTATIONAL EFFICIENCY; COMPUTER PROGRAMMING; GENETIC ALGORITHMS; NEURAL NETWORKS; SIMULATED ANNEALING;

CELLULAR MANUFACTURING;

EID: 79956103511     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2011.03.013     Document Type: Article

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