With the advancement of combat equipment technology and combat concepts,new requirements have been put forward for air defense operations during a group target attack.To achieve high-efficiency and lowloss defensive o...With the advancement of combat equipment technology and combat concepts,new requirements have been put forward for air defense operations during a group target attack.To achieve high-efficiency and lowloss defensive operations,a reasonable air defense weapon assignment strategy is a key step.In this paper,a multi-objective and multi-constraints weapon target assignment(WTA)model is established that aims to minimize the defensive resource loss,minimize total weapon consumption,and minimize the target residual effectiveness.An optimization framework of air defense weapon mission scheduling based on the multiobjective artificial bee colony(MOABC)algorithm is proposed.The solution for point-to-point saturated attack targets at different operational scales is achieved by encoding the nectar with real numbers.Simulations are performed for an imagined air defense scenario,where air defense weapons are saturated.The non-dominated solution sets are obtained by the MOABC algorithm to meet the operational demand.In the case where there are more weapons than targets,more diverse assignment schemes can be selected.According to the inverse generation distance(IGD)index,the convergence and diversity for the solutions of the non-dominated sorting genetic algorithm III(NSGA-III)algorithm and the MOABC algorithm are compared and analyzed.The results prove that the MOABC algorithm has better convergence and the solutions are more evenly distributed among the solution space.展开更多
Heritability estimates may be severely biased when a large common environmental effect on a family arises from a longlasting separate rearing at early stages(SRES)in traditional selective breeding programs,especially ...Heritability estimates may be severely biased when a large common environmental effect on a family arises from a longlasting separate rearing at early stages(SRES)in traditional selective breeding programs,especially when bred populations have weak genetic ties.Communal rearing at early stages(CRES)may reduce common environmental effect since all families are reared in the same environment immediately after hatching.Here,we compared the effects of CRES and SRES strategies on genetic parameter estimation for harvest body weight in a selective breeding population of Litopenaeus vannamei with a small number of half-sib families.Genetic parameters of each strategy were estimated by using animal models excluding and including the common environmental effect(Model 1 and Model 2,respectively).Heritability estimates for body weight were 0.21±0.06(P<0.05)and 0.69±0.09(P<0.05)for CRES and SRES,respectively,in Model 1,and 0.21±0.06(P<0.05)and 0.52±0.27(P>0.05)in Model 2.The ratio of common environmental variance to phenotypic variance was 0.002±0.000 and 0.071±0.112 for CRES and SRES,respectively.Neither strategy precisely partitioned the common environmental variance according to likelihood ratio test.Lower heritability for body weight in CRES than in SRES implied that a large common environmental variance was confounded with additive genetic variance and was not effectively partitioned in SRES.Moreover,genetic correlation of body weight between the two strategies was 0.75±0.15,indicating that family rankings truly changed.The CRES should be followed in the selective breeding program of shrimp,especially in a population with a shallow pedigree and weak genetic ties between families.展开更多
基金supported by the National Natural Science Foundation of China(71771216).
文摘With the advancement of combat equipment technology and combat concepts,new requirements have been put forward for air defense operations during a group target attack.To achieve high-efficiency and lowloss defensive operations,a reasonable air defense weapon assignment strategy is a key step.In this paper,a multi-objective and multi-constraints weapon target assignment(WTA)model is established that aims to minimize the defensive resource loss,minimize total weapon consumption,and minimize the target residual effectiveness.An optimization framework of air defense weapon mission scheduling based on the multiobjective artificial bee colony(MOABC)algorithm is proposed.The solution for point-to-point saturated attack targets at different operational scales is achieved by encoding the nectar with real numbers.Simulations are performed for an imagined air defense scenario,where air defense weapons are saturated.The non-dominated solution sets are obtained by the MOABC algorithm to meet the operational demand.In the case where there are more weapons than targets,more diverse assignment schemes can be selected.According to the inverse generation distance(IGD)index,the convergence and diversity for the solutions of the non-dominated sorting genetic algorithm III(NSGA-III)algorithm and the MOABC algorithm are compared and analyzed.The results prove that the MOABC algorithm has better convergence and the solutions are more evenly distributed among the solution space.
基金the National Key R&D Program of China(No.2018YFD0901301),the Shandong Province’s Agricultural Seed Improvement Project(No.2017LZN011)the Central Public-interest Scientific Institution Basal Research Fund,CAFS(No.20603022020003)+3 种基金the China Agriculture Research System(CARS-48)the Projects of International Exchange and Cooperation in Agriculture of Ministry of Agriculture and Rural Affairs of China–Science,Technology and Innovation Cooperation Cooperation in Aquaculture with Tropical Countriesthe Introduction of International Advanced Agricultural Science and Technology Plan of China(No.2016-X39)the Major Applied Technology Innovation Project of Agriculture in Shandong Province(No.SD2019YY001).
文摘Heritability estimates may be severely biased when a large common environmental effect on a family arises from a longlasting separate rearing at early stages(SRES)in traditional selective breeding programs,especially when bred populations have weak genetic ties.Communal rearing at early stages(CRES)may reduce common environmental effect since all families are reared in the same environment immediately after hatching.Here,we compared the effects of CRES and SRES strategies on genetic parameter estimation for harvest body weight in a selective breeding population of Litopenaeus vannamei with a small number of half-sib families.Genetic parameters of each strategy were estimated by using animal models excluding and including the common environmental effect(Model 1 and Model 2,respectively).Heritability estimates for body weight were 0.21±0.06(P<0.05)and 0.69±0.09(P<0.05)for CRES and SRES,respectively,in Model 1,and 0.21±0.06(P<0.05)and 0.52±0.27(P>0.05)in Model 2.The ratio of common environmental variance to phenotypic variance was 0.002±0.000 and 0.071±0.112 for CRES and SRES,respectively.Neither strategy precisely partitioned the common environmental variance according to likelihood ratio test.Lower heritability for body weight in CRES than in SRES implied that a large common environmental variance was confounded with additive genetic variance and was not effectively partitioned in SRES.Moreover,genetic correlation of body weight between the two strategies was 0.75±0.15,indicating that family rankings truly changed.The CRES should be followed in the selective breeding program of shrimp,especially in a population with a shallow pedigree and weak genetic ties between families.
