The year 2015 marks the 30th birthday of DC (Difference of Convex functions) programming
and DCA (DC Algorithms) which constitute the backbone of nonconvex programming and …

Optimization techniques are among the most promising methods to deal with real-world
problems, consisting of several objective functions and constraints. Over the decades, many …

DC (difference of convex functions) programming and DC algorithm (DCA) are powerful
tools for nonsmooth nonconvex optimization. This field was created in 1985 by Pham Dinh …

In this work, we propose a new approach called “Successive Linear Programming Algorithm
(SLPA)” for finding an approximate global minimizer of general nonconvex quadratic …

In this paper, we propose a clean and general proof framework to establish the convergence
analysis of the Difference-of-Convex (DC) programming algorithm (DCA) for both standard …

This paper proposes a novel Difference-of-Convex (DC) decomposition for polynomials
using a power-sum representation, achieved by solving a sparse linear system. We …

It is undoubtedly that mathematical modelling and optimisation play a key role in the supply
chain and the production management (SCPM). In this paper, we provide a survey on DC …

The Mean-Variance-Skewness-Kurtosis (MVSK) portfolio optimization model is a quartic
nonconvex polynomial minimization problem over a polytope, which can be formulated as a …

We are interested in developing a Difference-of-Convex (DC) programming approach based
on Difference-of-Convex-Sums-of-Squares (DC-SOS) decomposition techniques for high …

In this article, we discuss the numerical solution of Boolean polynomial programs by
algorithms borrowing from numerical methods for differential equations, namely the Houbolt …