Past performance is no guarantee of future results. Potential for profi t is accompanied by possibility of loss. Commodities trading involves substantial risk of loss. Introduction Essential Beta (EB) is an investment strategy designed to achieve equity like returns with balanced portfolio volatility and a low correlation to equities. It does so by selecting the liquid markets that are essentia...

The issue of financial integration, at the country level, is a well-documented phenomenon in the area of International Portfolio Diversification (IPD). Despite the increasing degree of financial integration, it is important to investigate the global integration at industry level to capture the potential benefits of IPD. Thus, this study attempts to evaluate the potential advantages of IPD for i...

Projection methods, which hold selected variables fixed while manipulating others, have a particularly useful role in metaheuristic procedures, especially in connection with large scale optimization and parallelization approaches. This role is enriched by adaptive memory processes of tabu search, which provide a collection of easily stated strategies to uncover improved solutions during the cou...

In this paper we present a new evolutionary method for complex-process optimization. It is partially based on principles of the scatter search methodology, but it makes use of innovative strategies to be more effective in the context of complex-process optimization using a small number of tuning parameters. In particular, we introduce a new combination method based on path relinking, which cons...

There is a variety of methods for ranking objectives in multiobjective optimization and some are difficult to define because they require information a priori (e.g. establishing weights in a weighted approach or setting the ordering in a lexicographic approach). In manyobjective optimization problems, those methods may exhibit poor diversification and intensification performance. We propose the...

This paper addresses the application of the principles of feedback and self-controlling software to the tabu search algorithm. We introduce two new reaction strategies for the tabu search algorithm. The first strategy treats the tabu search algorithm as a target system to be controlled and uses a control-theoretic approach to adjust the algorithm parameters that affect search intensification. T...

Optimization methods based on complete neighborhood exploration such as Tabu Search are impractical against large neighborhood problems. Strategies of candidate list propose a solution to reduce the neighborhood exploration complexity. We propose in this paper a generic Tabu Search algorithm using adaptive candidate list strategy based on two alternate candidate lists. Each candidate list strat...

We consider the problem of scheduling a number of jobs, each job having a release time, a processing time and a due date, on a single machine with the objective of minimizing the maximum lateness. We developed a hybrid dual-population genetic algorithm and compared its performance with alternative methods on a new diverse data set. Extensions from a single to a dual population by taking problem...

The search for efficient and reliable bio-inspired optimization methods continues to be an active topic of research due to the wide application of the developed methods. In this study, we developed a reliable and efficient optimization method via the hybridization of two bio-inspired swarm intelligence optimization algorithms, namely, the Monkey Algorithm (MA) and the Krill Herd Algorithm (KHA)...

Recently proved successful for variants of the vehicle routing problem (VRP) involving time windows, genetic algorithms have not yet shown to compete or challenge current best search techniques in solving the classical capacitated VRP. In this paper, a hybrid genetic algorithm to address the capacitated vehicle routing problem is proposed. The basic scheme consists in concurrently evolving two ...