Cite
A strongly convergent norm-relaxed method of strongly sub-feasible direction for optimization with nonlinear equality and inequality constraints
MLA
Jian, Jin-Bao, et al. “A Strongly Convergent Norm-Relaxed Method of Strongly Sub-Feasible Direction for Optimization with Nonlinear Equality and Inequality Constraints.” Applied Mathematics & Computation, vol. 182, no. 1, Nov. 2006, pp. 854–70. EBSCOhost, https://doi.org/10.1016/j.amc.2006.04.049.
APA
Jian, J.-B., Xu, Q.-J., & Han, D.-L. (2006). A strongly convergent norm-relaxed method of strongly sub-feasible direction for optimization with nonlinear equality and inequality constraints. Applied Mathematics & Computation, 182(1), 854–870. https://doi.org/10.1016/j.amc.2006.04.049
Chicago
Jian, Jin-Bao, Qing-Juan Xu, and Dao-Lan Han. 2006. “A Strongly Convergent Norm-Relaxed Method of Strongly Sub-Feasible Direction for Optimization with Nonlinear Equality and Inequality Constraints.” Applied Mathematics & Computation 182 (1): 854–70. doi:10.1016/j.amc.2006.04.049.