2025/01/08 by Adil Bagirov, Kaisa Joki, Bagirov, Adil M. +5
Computer Science · Engineering · Mathematics · #49J52 #65K05 #90C26 #90C59 #FOS: Mathematics #Low-power high-performance VLSI design #Matrix Theory and Algorithms #Numerical methods for differential equations #Optimization and Control (math.OC)
paper · pdf · doi:10.48550/arxiv.2501.04291
openalex publication_date 2025/01/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We consider the difference of convex (DC) optimization problem subject to box constraints. Utilizing epsilon-subdifferentials of DC components of the objective, we develop a new method for finding global solutions to this problem. The method combines a local search approach with a special procedure for escaping non-global solutions by identifying improved initial points for a local search. The method terminates when the solution cannot be improved further. The escaping procedure is designed using subsets of the epsilon-subdifferentials of DC components. We compute the deviation between these subsets and determine epsilon-subgradients, providing this deviation. Using these specific epsilon-subgradients, we formulate a subproblem with a convex objective function. The solution to this subproblem serves as a starting point for a local search. We study the convergence of the conceptual version of the proposed method and discuss its implementation. A large number of academic test problems demonstrate that the method requires reasonable computational effort to find higher-quality solutions than other local DC optimization methods. Additionally, we apply the new method to find global solutions to DC optimization problems and compare its performance with two benchmark global optimization solvers.