An Efficient Modified Particle Swarm Optimization Algorithm for Solving Mixed-Integer Nonlinear Programming Problems
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This paper presents a new algorithm for solving mixed integer nonlinear programming problems. The algorithm uses a branch and bound strategy where a nonlinear programming problem is solved in each integer node of the tree. The nonlinear programming problems, at each integer node
Many engineering design problems involve a combination of both continuous and discrete variables. However, the number of studies scarcely exceeds a few on mixed-variable problems. In this research Particle Swarm Optimization (PSO) algorithm is employed to solve mixedvariable nonl
This paper deals with the development of an efficient hybrid approach based on genetic algorithm and particle swarm optimization for solving mixed integer nonlinear reliability optimization problems in series, series–parallel and bridge systems. This approach maximizes the overal
Many engineering design problems involve a combination of both continuous anddiscrete variables. However, the number of studies scarcely exceeds a few on mixed-variableproblems. In this research Particle Swarm Optimization (PSO) algorithm is employed to solve mixedvariablenonline
Portfolio selection problems in investments are most studied in modern finance because of their computational intractability. The basic topic of modern portfolio theory is the way in which investors can construct a diversified portfolio of financial securities so as to achieve im
This special class of a nonlinear mathematical programming problem which is addressed in this paper has a structure characterized by a subset of variables restricted to assume discrete values, which are linear and separable from the continuous variables. The strategy of releasing