This paper presents two meta-heuristic algorithms to solve an extended portfolio selection model. The extended model is based on the Markowitz's Model, aiming to minimize investment risk in a specified level of return. In order to get the Markowitz model close to the real conditions, different constraints were embedded on the model which resulted in a discrete and non-convex solution space. ...

Stock price crash risk is a phenomenon in which stock prices are subject to severe negative and sudden adjustments. So far, different approaches have been proposed to model and predict  the  stock price crash risk, which in most cases have been the main emphasis on the factors affecting it, and often traditional methods have been used for prediction. On the other hand, using  Meta Heuristic Alg...

In this chapter the authors address a hybrid flow shop scheduling problem considering the minimization of the makespan in addition to the sum of earliness and tardiness penalties. This problem is proven to be NP-hard, and consequently the development of heuristic and meta-heuristic approaches to solve it is well justified. So, to deal with this problem, the authors propose a method which consis...

ARTICLE 1. Introduction Computational Grids (CGs) are a natural extension of classical distributed systems. CGs are expected to leverage unprecedented larger computing capacities by virtually joining together geographically distributed resources at large scale. To achieve this objective, the design of ecient Grid schedulers that map and allocate tasks and applications onto Grid resources is a k...

This thesis presents an investigation into the use of hyper-heuristic approaches to construct and improve solutions for exam timetabling problems. The majority of the approaches developed in the literature operate on a space of potential solutions to a problem. However, a hyper-heuristic is a heuristic which acts on a space of heuristics, rather than a solution space directly. The majority of r...

The development of modern wide-area power systems, as well as recent trends towards the creation of sustainable energy systems have given birth to complex studies addressing technical, but also economical and environmental, aspects related to simple or multi-objective optimization problems. Recently, heuristic and metaheuristic approaches that apply combinations of different heuristics with or ...

One of the main motivations for investigating hyper-heuristic methodologies is to provide a more general search framework than is currently available. Most of the current search techniques represent approaches that are largely adapted for specific search problems (and, in some cases, even specific problem instances). There are many real-world scenarios where the development of such bespoke syst...

Bridging the gap between simulation and reality for successful micro-grid (MG) implementation requires accurate mathematical modelling of underlying energy infrastructure extensive optimisation design space defined by all possible combinations size equipment. While exact approaches to MG capacity planning are highly computationally efficient, they often fail preserve associated problem nonlinea...