Generalized algorithms for solving problems of discrete, integer, and Boolean programming are discussed. These algorithms are associated with the method of normalized functions and are based on a combination of formal...Generalized algorithms for solving problems of discrete, integer, and Boolean programming are discussed. These algorithms are associated with the method of normalized functions and are based on a combination of formal and heuristic procedures. This allows one to obtain quasi-optimal solutions after a small number of steps, overcoming the NP-completeness of discrete optimization problems. Questions of constructing so-called “duplicate” algorithms are considered to improve the quality of discrete problem solutions. An approach to solving discrete problems with fuzzy coefficients in objective functions and constraints on the basis of modifying the generalized algorithms is considered. Questions of applying the generalized algorithms to solve multicriteria discrete problems are also discussed. The results of the paper are of a universal character and can be applied to the design, planning, operation, and control of systems and processes of different purposes. The results of the paper are already being used to solve power engineering problems.展开更多
In this paper, first, a biobjective thermodynamics model of minimizing comprehensive quantity of boiler vapour consumption and maximizing thermodynamics efficiency of an absorption refrigeration system is established,...In this paper, first, a biobjective thermodynamics model of minimizing comprehensive quantity of boiler vapour consumption and maximizing thermodynamics efficiency of an absorption refrigeration system is established, solved by a multiobjective optimization method to generate a non-inferior scheme set. Then, applying fuzzy multicriterion decision method, a best compromise scheme is selected by taking account of five factors-investment, operation cost, total water consumption, compactness of apparatus and difficulty of operation and maintenance. In addition, other complex factors are considered simultaneously which can hardly be treated by classical methods. The decision thought and method in this paper is of certain universal significance to problems of scheme optimization.展开更多
文摘Generalized algorithms for solving problems of discrete, integer, and Boolean programming are discussed. These algorithms are associated with the method of normalized functions and are based on a combination of formal and heuristic procedures. This allows one to obtain quasi-optimal solutions after a small number of steps, overcoming the NP-completeness of discrete optimization problems. Questions of constructing so-called “duplicate” algorithms are considered to improve the quality of discrete problem solutions. An approach to solving discrete problems with fuzzy coefficients in objective functions and constraints on the basis of modifying the generalized algorithms is considered. Questions of applying the generalized algorithms to solve multicriteria discrete problems are also discussed. The results of the paper are of a universal character and can be applied to the design, planning, operation, and control of systems and processes of different purposes. The results of the paper are already being used to solve power engineering problems.
文摘In this paper, first, a biobjective thermodynamics model of minimizing comprehensive quantity of boiler vapour consumption and maximizing thermodynamics efficiency of an absorption refrigeration system is established, solved by a multiobjective optimization method to generate a non-inferior scheme set. Then, applying fuzzy multicriterion decision method, a best compromise scheme is selected by taking account of five factors-investment, operation cost, total water consumption, compactness of apparatus and difficulty of operation and maintenance. In addition, other complex factors are considered simultaneously which can hardly be treated by classical methods. The decision thought and method in this paper is of certain universal significance to problems of scheme optimization.
