The whole metazoan community inhabiting Laizhou Bay and adjacent Bohai Sea waters were sampled in late autumn, 2006. Secondary production estimates for macrofauna and meiofauna were made separately. Total benthic seco...The whole metazoan community inhabiting Laizhou Bay and adjacent Bohai Sea waters were sampled in late autumn, 2006. Secondary production estimates for macrofauna and meiofauna were made separately. Total benthic secondary production was as high as 8.38 ±4.08 g ash-free dry weight （AFDW） m^-2 a^-1, which represented the autumn production level. In general, macrofaunal secondary production in Laizhou Bay was much lower than that in adjacent Bohai Sea areas. In contrast, meiofaunal secondary production in Laizhou Bay was higher than that in adjacent Bohai Sea areas. Macrofatma contributed 61% to benthic secondary production （5.09 ±3.26 g AFDW m^-2 a^-1）, lower than the value in previous studies in Bohai Sea. Sediment granulometric characteristics and bottom-water salinity could explain the substantial variability in the macrofauna biomass and production. Meiofaunal production was an important component of benthic production and exceeded macrofauna production under exceptional conditions, e.g. in Laizhou Bay, where macrofauna was restricted. Chlorophyll pigments （Chl-a） concentrations in sediment explained the general meiofaunal biomass and production distribution here.展开更多
This paper treats multi-objective problem for manufacturing process design. A purpose of the process design is to decide combinations of work elements assigned to different work centers. Multiple work elements are ord...This paper treats multi-objective problem for manufacturing process design. A purpose of the process design is to decide combinations of work elements assigned to different work centers. Multiple work elements are ordinarily assigned to each center. Here, infeasible solutions are easily generated by precedence relationship of work elements in process design. The number of infeasible solutions generated is ordinarily larger than that of feasible solutions generated in the process. Therefore, feasible and infeasible solutions are located in any neighborhood in solution space. It is difficult to seek high quality Pareto solutions in this problem by using conventional multi-objective evolutional algorithms. We consider that the problem includes difficulty to seek high quality solutions by the following characteristics： （1） Since infeasible solutions are resemble to good feasible solutions, many infeasible solutions which have good values of objective functions are easily sought in the search process, （2） Infeasible solutions are useful to select new variable conditions generating good feasible solutions in search process. In this study, a multi-objective genetic algorithm including local search is proposed using these characteristics. Maximum value of average operation times and maximum value of dispersion of operation time in all work centers are used as objective functions to promote productivity. The optimal weighted coefficient is introduced to control the ratio of feasible solutions to all solutions selected in crossover and selection process in the algorithm. This paper shows the effectiveness of the proposed algorithm on simple model.展开更多
基金supported by the National Natural Science Foundation of China (Nos 40730847, 40906063)
文摘The whole metazoan community inhabiting Laizhou Bay and adjacent Bohai Sea waters were sampled in late autumn, 2006. Secondary production estimates for macrofauna and meiofauna were made separately. Total benthic secondary production was as high as 8.38 ±4.08 g ash-free dry weight （AFDW） m^-2 a^-1, which represented the autumn production level. In general, macrofaunal secondary production in Laizhou Bay was much lower than that in adjacent Bohai Sea areas. In contrast, meiofaunal secondary production in Laizhou Bay was higher than that in adjacent Bohai Sea areas. Macrofatma contributed 61% to benthic secondary production （5.09 ±3.26 g AFDW m^-2 a^-1）, lower than the value in previous studies in Bohai Sea. Sediment granulometric characteristics and bottom-water salinity could explain the substantial variability in the macrofauna biomass and production. Meiofaunal production was an important component of benthic production and exceeded macrofauna production under exceptional conditions, e.g. in Laizhou Bay, where macrofauna was restricted. Chlorophyll pigments （Chl-a） concentrations in sediment explained the general meiofaunal biomass and production distribution here.
文摘This paper treats multi-objective problem for manufacturing process design. A purpose of the process design is to decide combinations of work elements assigned to different work centers. Multiple work elements are ordinarily assigned to each center. Here, infeasible solutions are easily generated by precedence relationship of work elements in process design. The number of infeasible solutions generated is ordinarily larger than that of feasible solutions generated in the process. Therefore, feasible and infeasible solutions are located in any neighborhood in solution space. It is difficult to seek high quality Pareto solutions in this problem by using conventional multi-objective evolutional algorithms. We consider that the problem includes difficulty to seek high quality solutions by the following characteristics： （1） Since infeasible solutions are resemble to good feasible solutions, many infeasible solutions which have good values of objective functions are easily sought in the search process, （2） Infeasible solutions are useful to select new variable conditions generating good feasible solutions in search process. In this study, a multi-objective genetic algorithm including local search is proposed using these characteristics. Maximum value of average operation times and maximum value of dispersion of operation time in all work centers are used as objective functions to promote productivity. The optimal weighted coefficient is introduced to control the ratio of feasible solutions to all solutions selected in crossover and selection process in the algorithm. This paper shows the effectiveness of the proposed algorithm on simple model.
