In order to incorporate the decision maker＇s preference into multiobjective optimization a preference-based multiobjective artificial bee colony algorithm PMABCA is proposed.In the proposed algorithm a novel referenc...In order to incorporate the decision maker＇s preference into multiobjective optimization a preference-based multiobjective artificial bee colony algorithm PMABCA is proposed.In the proposed algorithm a novel reference point based preference expression method is addressed.The fitness assignment function is defined based on the nondominated rank and the newly defined preference distance.An archive set is introduced for saving the nondominated solutions and an improved crowding-distance operator is addressed to remove the extra solutions in the archive.The experimental results of two benchmark test functions show that a preferred set of solutions and some other non-preference solutions are achieved simultaneously.The simulation results of the proportional-integral-derivative PID parameter optimization for superheated steam temperature verify that the PMABCA is efficient in aiding to making a reasonable decision.展开更多
Methods to optimize the production of gamma-aminobutyric acid （GABA） by Lactobacillus brevis CGMCC 1306 were investigated. Results indicated that cell growth was maximal at pH 5.0, while pH 4.5 was pref-erable to GA...Methods to optimize the production of gamma-aminobutyric acid （GABA） by Lactobacillus brevis CGMCC 1306 were investigated. Results indicated that cell growth was maximal at pH 5.0, while pH 4.5 was pref-erable to GABA formation. The optimal temperature for cell growth （35 °C） was lower than that for GABA forma-tion （40 °C）. In a two-stage pH and temperature control fermentation, cultures were maintained at pH 5.0 and 35 °C for 32 h, then adjusted to pH 4.5 and 40 °C, GABA production increased remarkably and reached 474.79 mmol·L-1 at 72 h, while it was 398.63 mmol·L-1 with one stage pH and temperature control process, in which cultivation con-ditions were constantly controlled at pH 5.0 and 35 °C. In order to avoid the inhibition of cell growth at higher L-monosodium glutamate （L-MSG） concentrations, the two-stage control fermentation with substrate feeding strat-egy was applied to GABA production, with 106.87 mmol （20 g） L-MSG supplemented into the shaking-flask at 32 h and 56 h post-inoculation separately. The GABA concentration reached 526.33 mmol·L-1 at 72 h with the fer-mentation volume increased by 38%. These results will provide primary data to realize large-scale production of GABA by L. brevis CGMCC 1306.展开更多
The main objective of this study is the control of the agricultural greenhouse in view of the economic interest generated by such an activity. A simulation model is developed, gathering all the external and internal c...The main objective of this study is the control of the agricultural greenhouse in view of the economic interest generated by such an activity. A simulation model is developed, gathering all the external and internal climatic conditions that influence the microclimate of the greenhouse to predict the temporal evolution of the state variables characterizing this microclimate. The fuzzy control is an alternative to the approaches proposed by the automatic for the control of complex systems. The performance objectives of the looped systems and the corresponding actions are summarized in the form of rules of expertise, which are spelled out in plain language. This technique thus makes it possible to dispense with the use of mathematical models which are sometimes difficult to obtain. Our objective is the multivariable strategy synthesis and the fuzzy application to a multivariate system （MIMO ~ such as the agricultural greenhouse.） First, the principles of fuzzy logic and fuzzy control are recalled. The origins of non-Linearitys of the command are explained. One of the practical problems of this technique is the combinatorial explosion of the rule base when the number of variables involved becomes large. A solution to simplify the complexity of the system is presented together with an optimization algorithm to automatically adjust the parameters of the fuzzy controller. The last part is devoted to the synthesis of an optimal control of the greenhouse in order to compare it to the fuzzy control implemented.展开更多
基金The National Natural Science Foundation of China(No.51306082,51476027)
文摘In order to incorporate the decision maker＇s preference into multiobjective optimization a preference-based multiobjective artificial bee colony algorithm PMABCA is proposed.In the proposed algorithm a novel reference point based preference expression method is addressed.The fitness assignment function is defined based on the nondominated rank and the newly defined preference distance.An archive set is introduced for saving the nondominated solutions and an improved crowding-distance operator is addressed to remove the extra solutions in the archive.The experimental results of two benchmark test functions show that a preferred set of solutions and some other non-preference solutions are achieved simultaneously.The simulation results of the proportional-integral-derivative PID parameter optimization for superheated steam temperature verify that the PMABCA is efficient in aiding to making a reasonable decision.
基金Supported by the National＇Naturai Science Foundation of China （30970638, 21176220 and 31240054）, Zhejiang Provincial Natural Science Foundation （Z13B06008） and the National Basic Research Program of China （2007CB714305）.
文摘Methods to optimize the production of gamma-aminobutyric acid （GABA） by Lactobacillus brevis CGMCC 1306 were investigated. Results indicated that cell growth was maximal at pH 5.0, while pH 4.5 was pref-erable to GABA formation. The optimal temperature for cell growth （35 °C） was lower than that for GABA forma-tion （40 °C）. In a two-stage pH and temperature control fermentation, cultures were maintained at pH 5.0 and 35 °C for 32 h, then adjusted to pH 4.5 and 40 °C, GABA production increased remarkably and reached 474.79 mmol·L-1 at 72 h, while it was 398.63 mmol·L-1 with one stage pH and temperature control process, in which cultivation con-ditions were constantly controlled at pH 5.0 and 35 °C. In order to avoid the inhibition of cell growth at higher L-monosodium glutamate （L-MSG） concentrations, the two-stage control fermentation with substrate feeding strat-egy was applied to GABA production, with 106.87 mmol （20 g） L-MSG supplemented into the shaking-flask at 32 h and 56 h post-inoculation separately. The GABA concentration reached 526.33 mmol·L-1 at 72 h with the fer-mentation volume increased by 38%. These results will provide primary data to realize large-scale production of GABA by L. brevis CGMCC 1306.
文摘The main objective of this study is the control of the agricultural greenhouse in view of the economic interest generated by such an activity. A simulation model is developed, gathering all the external and internal climatic conditions that influence the microclimate of the greenhouse to predict the temporal evolution of the state variables characterizing this microclimate. The fuzzy control is an alternative to the approaches proposed by the automatic for the control of complex systems. The performance objectives of the looped systems and the corresponding actions are summarized in the form of rules of expertise, which are spelled out in plain language. This technique thus makes it possible to dispense with the use of mathematical models which are sometimes difficult to obtain. Our objective is the multivariable strategy synthesis and the fuzzy application to a multivariate system （MIMO ~ such as the agricultural greenhouse.） First, the principles of fuzzy logic and fuzzy control are recalled. The origins of non-Linearitys of the command are explained. One of the practical problems of this technique is the combinatorial explosion of the rule base when the number of variables involved becomes large. A solution to simplify the complexity of the system is presented together with an optimization algorithm to automatically adjust the parameters of the fuzzy controller. The last part is devoted to the synthesis of an optimal control of the greenhouse in order to compare it to the fuzzy control implemented.
