Andrea Villagra

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Absrracr: Dynamic scheduling can be classified as partial or total. In simplest partially dynamic problems the only unknown attribute of a jab is its arrival time '/. In some totally dynamic problems, other job attributes such as processing time ph due date d, and weights w,, are also unknown until processing. This paper proposes two approaches to face(More)
A cellular genetic algorithm (cGA) is a powerful metaheuristic that has been successfully used since its creation to solve optimization problems.Over the past fewyears, interest in hybrid metaheuristics has also grown considerably. Research into cross fertilization between algorithms has provided extremely efficient search techniques in the past. In this(More)
Estimation of Distribution Algorithms (EDAs) are stochastic optimization techniques that explore the space of potential solutions by building and sampling explicit probabilistic models of promising candidate solutions. EDAs provide scalable solutions to many problems that are intractable with other techniques, solving enormously complex problems that often(More)
This work presents the results of a new methodology for hybridizing metaheuristics. By first locating the active components (parts) of one algorithm and then inserting them into second one, we can build efficient and accurate optimization, search, and learning algorithms. This gives a concrete way of constructing new techniques that contrasts the spread ad(More)