In this paper we compare the performance of the Differential Evolution (DE) and the Repulsive Particle Swarm (RPS) methods of global optimization. To this end, seventy test functions have been chosen. Among these test functions, some are new while others are well known in the literature; some are...

The method of forecasting seasonal demand applying genetic algorithm is presented. Specific form of used demand function is shown in the first section of the article. Next the method of identification of the function parameters using genetic algorithms is discussed. In the final section an...

The design of supply chain networks subject to disruptions is tackled. A genetic algorithm with the objective of minimizing the design cost and regret cost is developed to achieve a reliable supply chain network. The improvement of supply chain network reliability is measured against the supply...

The selection of optimal portfolios is the central problem of financial investment decisions. Mathematically speaking, portfolio selection refers to the formulation of an objective function that determines the weights of the portfolio invested in each asset as to maximize return and minimize...

The objective of this paper is to develop an algorithm to create an Optimum Portfolio from a large pool of stocks listed in a single market index SPX 500 Index: USA (for example) using Genetic Algorithm. The algorithm selects stocks on the basis of a priority index function designed on company...

The nearest correlation matrix problem is to find a valid (positive semidefinite) correlation matrix, R(m,m), that is nearest to a given invalid (negative semidefinite) or pseudo-correlation matrix, Q(m,m); m larger than 2. In the literature on this problem, 'nearest' is invariably defined in...