User Objects are the basement in developing distributed PowerBuilder applications. There are two kinds of PowerBuilder objects: visual objects and non-visual objects. Usually we use non-visual objects to perform the P...User Objects are the basement in developing distributed PowerBuilder applications. There are two kinds of PowerBuilder objects: visual objects and non-visual objects. Usually we use non-visual objects to perform the PowerBuilder distriuted application. This paper introduces the method of developing PowerBuilder distributed application program, mainly discusses the application of nonvisual objects when developing PowerBuilder distributed application programs.展开更多
A primal-dual infeasible interior point algorithm for multiple objective linear programming (MOLP) problems was presented. In contrast to the current MOLP algorithm. moving through the interior of polytope but not con...A primal-dual infeasible interior point algorithm for multiple objective linear programming (MOLP) problems was presented. In contrast to the current MOLP algorithm. moving through the interior of polytope but not confining the iterates within the feasible region in our proposed algorithm result in a solution approach that is quite different and less sensitive to problem size, so providing the potential to dramatically improve the practical computation effectiveness.展开更多
文摘User Objects are the basement in developing distributed PowerBuilder applications. There are two kinds of PowerBuilder objects: visual objects and non-visual objects. Usually we use non-visual objects to perform the PowerBuilder distriuted application. This paper introduces the method of developing PowerBuilder distributed application program, mainly discusses the application of nonvisual objects when developing PowerBuilder distributed application programs.
基金Supported by the Doctoral Educational Foundation of China of the Ministry of Education(20020486035)
文摘A primal-dual infeasible interior point algorithm for multiple objective linear programming (MOLP) problems was presented. In contrast to the current MOLP algorithm. moving through the interior of polytope but not confining the iterates within the feasible region in our proposed algorithm result in a solution approach that is quite different and less sensitive to problem size, so providing the potential to dramatically improve the practical computation effectiveness.
