Allameh Tabataba'i UniversityIndustrial Management Studies2251-802951420061222A mixed Genetic Algorithm and Simulated annealing Algorithm for Cattle Food production process optimizationA mixed Genetic Algorithm and Simulated annealing Algorithm for Cattle Food production process optimization2512734418FAMaghsoudAmiri0000-0002-0650-2584SaraHatamiSeyed MostafaMoosaviJournal Article20090502In this paper we try to determine optimal combination of effective factors to produce cattle feed. Cattle feed has direct relation with cattle health, this research is done on real case study, therefore the gained results could be too important. Both response surface methodology and design of experiments are used for modeling and improving cattle feed production process which has more than one effective factor. After effective factors identification, designing of experiments will be done by central composite design. Interference factors, effective and independent parameters are inspected by forward method and finally a model is obtained by independent parameters. Because of continuous space of the problem and nonlinear objective functions a metaheuristics named "genetic annealing" is used to solve the problem. Proposed algorithm searched the solution space parallel. Another algorithm, simulated annealing is also proposed to evaluate the performances of two algorithms by improvement percent between initial and final result.In this paper we try to determine optimal combination of effective factors to produce cattle feed. Cattle feed has direct relation with cattle health, this research is done on real case study, therefore the gained results could be too important. Both response surface methodology and design of experiments are used for modeling and improving cattle feed production process which has more than one effective factor. After effective factors identification, designing of experiments will be done by central composite design. Interference factors, effective and independent parameters are inspected by forward method and finally a model is obtained by independent parameters. Because of continuous space of the problem and nonlinear objective functions a metaheuristics named "genetic annealing" is used to solve the problem. Proposed algorithm searched the solution space parallel. Another algorithm, simulated annealing is also proposed to evaluate the performances of two algorithms by improvement percent between initial and final result.https://jims.atu.ac.ir/article_4418_e2ad2c1ca300298bb31498b320b28022.pdf