The fuzzy goal flexible job-shop scheduling problem （FGFJSP） is the extension of FJSP. Compared with the convention JSP, it can solve the fuzzy goal problem and meet suit requirements of the key job. The multi-objec...The fuzzy goal flexible job-shop scheduling problem （FGFJSP） is the extension of FJSP. Compared with the convention JSP, it can solve the fuzzy goal problem and meet suit requirements of the key job. The multi-object problem, such as the fuzzy cost, the fuzzy due-date, and the fuzzy makespan, etc, can be solved by FGFJSP. To optimize FGFJSP, an individual optimization and colony diversity genetic algorithm （IOCDGA） is presented to accelerate the convergence speed and to avoid the earliness. In IOCDGA, the colony average distance and the colony entropy are defined after the definition of the encoding model. The colony diversity is expressed by the colony average distance and the colony entropy. The crossover probability and the mutation probability are controlled by the colony diversity. The evolution emphasizes that sigle individual or a few individuals evolve into the best in IOCDGA, but not the all in classical GA. Computational results show that the algorithm is applicable and the number of iterations is less.展开更多
In the flexible job-shop scheduling problem （FJSP）, each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objectiv...In the flexible job-shop scheduling problem （FJSP）, each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objective FJSP, the Grantt graph oriented string representation （GOSR） and the basic manipulation of the genetic algorithm operator are presented. An integrated operator genetic algorithm （IOGA） and its process are described. Comparison between computational results and the latest research shows that the proposed algorithm is effective in reducing the total workload of all machines, the makespan and the critical machine workload.展开更多
The optimiz at ion operation of gas pipeline network is investigated in this paper. Based on th e theories of system optimization and the multi object decision, a mathematical model about the multi object optimization...The optimiz at ion operation of gas pipeline network is investigated in this paper. Based on th e theories of system optimization and the multi object decision, a mathematical model about the multi object optimization operation of gas pipeline network is established, in line with the demand of urban gas pipeline network operation. A t the same time, an effective solution of the mathematical model is presented. A calculating software about optimization operation is compiled, coupling the actual operation of gas pipeline network. It can be applied to the operation of the gas pipeline network. The software was examined by real examples. The resul ts indicated that 2.13% energy consumption and 3.12% gas supply cost can be reduced through optimization operation.展开更多
文摘The fuzzy goal flexible job-shop scheduling problem （FGFJSP） is the extension of FJSP. Compared with the convention JSP, it can solve the fuzzy goal problem and meet suit requirements of the key job. The multi-object problem, such as the fuzzy cost, the fuzzy due-date, and the fuzzy makespan, etc, can be solved by FGFJSP. To optimize FGFJSP, an individual optimization and colony diversity genetic algorithm （IOCDGA） is presented to accelerate the convergence speed and to avoid the earliness. In IOCDGA, the colony average distance and the colony entropy are defined after the definition of the encoding model. The colony diversity is expressed by the colony average distance and the colony entropy. The crossover probability and the mutation probability are controlled by the colony diversity. The evolution emphasizes that sigle individual or a few individuals evolve into the best in IOCDGA, but not the all in classical GA. Computational results show that the algorithm is applicable and the number of iterations is less.
文摘In the flexible job-shop scheduling problem （FJSP）, each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objective FJSP, the Grantt graph oriented string representation （GOSR） and the basic manipulation of the genetic algorithm operator are presented. An integrated operator genetic algorithm （IOGA） and its process are described. Comparison between computational results and the latest research shows that the proposed algorithm is effective in reducing the total workload of all machines, the makespan and the critical machine workload.
文摘The optimiz at ion operation of gas pipeline network is investigated in this paper. Based on th e theories of system optimization and the multi object decision, a mathematical model about the multi object optimization operation of gas pipeline network is established, in line with the demand of urban gas pipeline network operation. A t the same time, an effective solution of the mathematical model is presented. A calculating software about optimization operation is compiled, coupling the actual operation of gas pipeline network. It can be applied to the operation of the gas pipeline network. The software was examined by real examples. The resul ts indicated that 2.13% energy consumption and 3.12% gas supply cost can be reduced through optimization operation.
