Three Search Algorithms for Three Nonconvex Optimization Problems

Alternative characterizations of three bargaining solutions for nonconvex problems

This paper studies compact and comprehensive bargaining problems for n players and axiomatically characterize the extensions of the three classical bargaining solutions to nonconvex bargaining problems: the Nash solution, the egalitarian solution and the Kalai-Smorodinsky solution. Our characterizing axioms are various extensions of Nash’s original axioms. ∗ We are grateful to the referee and t...

Heuristic optimization methods for three matrix problems

CHAOS EMBEDDED CHARGED SYSTEM SEARCH FOR PRACTICAL OPTIMIZATION PROBLEMS

Chaos is embedded to the he Charged System Search (CSS) to solve practical optimization problems. To improve the ability of global search, different chaotic maps are introduced and three chaotic-CSS methods are developed. A comparison of these variants and the standard CSS demonstrates the superiority and suitability of the selected variants for practical civil optimization problems.

Robust Nonconvex Optimization for Simulation-based Problems

In engineering design, an optimized solution often turns out to be suboptimal, when implementation errors are encountered. While the theory of robust convex optimization has taken significant strides over the past decade, all approaches fail if the underlying cost function is not explicitly given; it is even worse if the cost function is nonconvex. In this work, we present a robust optimization...

Nonconvex Robust Optimization for Problems with Constraints

W propose a new robust optimization method for problems with objective functions that may be computed via numerical simulations and incorporate constraints that need to be feasible under perturbations. The proposed method iteratively moves along descent directions for the robust problem with nonconvex constraints and terminates at a robust local minimum. We generalize the algorithm further to m...