This paper analyzes the pipe network system of oil-gas collection and transportation for offshore oilfield development. A '0-1' integer linear programming model is constructed to optimize the investment of sea...This paper analyzes the pipe network system of oil-gas collection and transportation for offshore oilfield development. A '0-1' integer linear programming model is constructed to optimize the investment of seabed pipe network. The mathematical model is solved by the spanning tree method of graph theory and network analysis. All spanning trees of a network graph compose all the feasible solutions of the mathematical model. The optimal solution of the model is the spanning tree with the minimum cost among all spanning trees. This method can be used to optimize the seabed pipe network system and give a minimum cost plan for the development of offshore marginal oilfield groups.展开更多
In this paper we present two-level linear programming method for determining latest dates and slack times in project network models with triangular fuzzy number or trapezoidal fuzzy number. Compared with the well-know...In this paper we present two-level linear programming method for determining latest dates and slack times in project network models with triangular fuzzy number or trapezoidal fuzzy number. Compared with the well-known fuzzy network techniques in literature, the approach always produces the meaningful latest dates and slack times. Practically we have generalized critical path method by accepting imprecise, fuzzy data for the duration of the activities.展开更多
OBJECTIVE One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the yield of an expected end product.METHDOS Metabolic control analysis(MCA)performs...OBJECTIVE One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the yield of an expected end product.METHDOS Metabolic control analysis(MCA)performs such role to calculate the sensitivity of flux change upon that of enzymes under the framework of ordinary differential equation(ODE)models,which are restricted in small-scale networks and require explicit kinetic parameters.The constraint-based models,like flux balance analysis(FBA),lack of the room of performing MCA because they are parameters-free.In this study,we developed a hyper-cube shrink algorithm(HCSA)to incorporate the enzymatic properties to the FBA model by introducing a pair of parameters for each reaction.Our algorithm was able to handle not only prediction of knockout strains but also strains with an adjustment of expression level of certain enzymes.RESULTS We first showed the concept by applying HCSA to a simplest three-nodes network.Then we show the HCSA possesses Michaelis-Menten like behaviors characterized by steady state of ODE.We obtained good prediction of a synthetic network in Saccharomyces cerevisiae producing voilacein and analogues.Finally we showed its capability of predicting the flux distribution in genome-scale networks by applying it to sporulation in yeast.CONCLUSION We have developed an algorithm the impact on fluxes when certain enzymes were inhibited or activated.It provides us a powerful tool to evaluate the consequences of enzyme inhibitor or activator.展开更多
文摘This paper analyzes the pipe network system of oil-gas collection and transportation for offshore oilfield development. A '0-1' integer linear programming model is constructed to optimize the investment of seabed pipe network. The mathematical model is solved by the spanning tree method of graph theory and network analysis. All spanning trees of a network graph compose all the feasible solutions of the mathematical model. The optimal solution of the model is the spanning tree with the minimum cost among all spanning trees. This method can be used to optimize the seabed pipe network system and give a minimum cost plan for the development of offshore marginal oilfield groups.
文摘In this paper we present two-level linear programming method for determining latest dates and slack times in project network models with triangular fuzzy number or trapezoidal fuzzy number. Compared with the well-known fuzzy network techniques in literature, the approach always produces the meaningful latest dates and slack times. Practically we have generalized critical path method by accepting imprecise, fuzzy data for the duration of the activities.
基金Supported by the National Basic Research Program of China under Grant No.2006CB303004 (国家重点基础研究发展计划(973))the National Natural Science Foundation of China under Grant Nos.60673154, 60573131 (国家自然科学基金)+1 种基金the Natural Science Foundation of Jiangsu Province of China under Grant No.BK2005411 (江苏省自然科学基金)the Jiangsu High-Tech Research Project of China under Grant No.BG2007391 (江苏省高技术研究计划)
基金The project supported by 985 Startup Funding in PKU
文摘OBJECTIVE One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the yield of an expected end product.METHDOS Metabolic control analysis(MCA)performs such role to calculate the sensitivity of flux change upon that of enzymes under the framework of ordinary differential equation(ODE)models,which are restricted in small-scale networks and require explicit kinetic parameters.The constraint-based models,like flux balance analysis(FBA),lack of the room of performing MCA because they are parameters-free.In this study,we developed a hyper-cube shrink algorithm(HCSA)to incorporate the enzymatic properties to the FBA model by introducing a pair of parameters for each reaction.Our algorithm was able to handle not only prediction of knockout strains but also strains with an adjustment of expression level of certain enzymes.RESULTS We first showed the concept by applying HCSA to a simplest three-nodes network.Then we show the HCSA possesses Michaelis-Menten like behaviors characterized by steady state of ODE.We obtained good prediction of a synthetic network in Saccharomyces cerevisiae producing voilacein and analogues.Finally we showed its capability of predicting the flux distribution in genome-scale networks by applying it to sporulation in yeast.CONCLUSION We have developed an algorithm the impact on fluxes when certain enzymes were inhibited or activated.It provides us a powerful tool to evaluate the consequences of enzyme inhibitor or activator.
