Generation scheduling (GS) in power systems is a tough optimisation problem which continues to present a challenge for efficient solution techniques. The solution is to define on/off decisions and generation levels for each electricity generator of a power system for each scheduling interval. The solution procedure requires simultaneous consideration of binary decision and continuous variables....

Recurrent neural network (RNN) has been widely used as a tool in the data classification. This network can be educated with gradient descent back propagation. However, traditional training algorithms have some drawbacks such as slow speed of convergence being not definite to find the global minimum of the error function since gradient descent may get stuck in local minima. As a solution, nature...

Portfolio selection is concerned with selecting from of a universe of assets the ones in which one wishes to invest and the amount of the investment. Several criteria can be used for portfolio selection, and the resulting approaches can be classified as being either active or passive. The two approaches are thought to be mutually exclusive, but some authors have suggested combining them in a un...

In this paper we focus on approximate solutions to solve a new class of Art Gallery Problems inspired by wireless localization. Instead of the usual guards we consider wireless devices whose signal can cross a certain number, k, of walls. These devices are called k-transmitters. We propose an algorithm for constructing the visibility region of a k-transmitter located on a point of a simple poly...

In this paper, a Goal Programming (GP) model is converted into a multi-objective optimization problem (MOO) of minimizing deviations from fixed goals. To solve the resulting MOO problem, a hybrid metaheuristic with two steps is proposed to find the Pareto set’s solutions. First, a Record-to-Record Travel with an adaptive memory is used to find first non-dominated Pareto frontier solutions preem...

The dynamic nature of grid resources and the demands of users produce complexity in the grid scheduling problem that cannot be addressed by deterministic algorithms with polynomial complexity. One of the best methods for grid scheduling is the genetic algorithm (GA); the simple and parallel features of this algorithm make it applicable to several optimization problems. A GA searches the problem...

The Traveling Salesman Problem (TSP) is one of the most challenging problems in Logistics and Supply Chain Management. Its relevance in routing planning and distribution has significant impact on reduction of operative costs for all enterprises. However, due to its NP-hard complexity, it is difficult to obtain optimal solutions for TSP instances. This paper describes a hybrid approach based on ...

This paper presents an improved harmony search metaheuristic for the multi-mode resource-constrained project scheduling problem (MRCPSP). The hybrid metaheuristic presented is an improved version of the forbidden set oriented “Sounds of Silence” harmony search metaheuristic. In the original approach a simple but efficient "rule of thumb" was applied to eliminate the hidden resource conflicts. T...