A class of functions called quasi B s invex and pseudo B s invex functions are introduced by using the concept of symmetric gradient. The examples of quasi B s invex and pseudo B s invex functions are given. The suffi...A class of functions called quasi B s invex and pseudo B s invex functions are introduced by using the concept of symmetric gradient. The examples of quasi B s invex and pseudo B s invex functions are given. The sufficient optimality conditions and Mond Weir type duality results are obtained for a nondifferentiable nonlinear semi infinite programming problem involving quasi B s invex and pseudo B s invex functions.展开更多
To describe the earliness/tardiness production planning problems in the JIT environment, a nonlinear semi\|infinite programming model was proposed in \. Due to a nonconvex objective function and many infinite constrai...To describe the earliness/tardiness production planning problems in the JIT environment, a nonlinear semi\|infinite programming model was proposed in \. Due to a nonconvex objective function and many infinite constraints, the model is difficult to be solved by traditional methods. In this paper, simulated annealing method combined with a heuristic is developed. Numerical results shows that the present approach is very efficient. Theoretically, the developed method is an attempt to solve a continuous domain problem by using simulated annealing.展开更多
基金the Natural Science Foundation of Shaanxi Province and the Science Foundation of Shaanxi Provincial Educational CommitteeP.R.China
文摘A class of functions called quasi B s invex and pseudo B s invex functions are introduced by using the concept of symmetric gradient. The examples of quasi B s invex and pseudo B s invex functions are given. The sufficient optimality conditions and Mond Weir type duality results are obtained for a nondifferentiable nonlinear semi infinite programming problem involving quasi B s invex and pseudo B s invex functions.
文摘To describe the earliness/tardiness production planning problems in the JIT environment, a nonlinear semi\|infinite programming model was proposed in \. Due to a nonconvex objective function and many infinite constraints, the model is difficult to be solved by traditional methods. In this paper, simulated annealing method combined with a heuristic is developed. Numerical results shows that the present approach is very efficient. Theoretically, the developed method is an attempt to solve a continuous domain problem by using simulated annealing.
