In today’s computer architectures the design spaces are huge, thus making it very difficult to find optimal configurations. One way to cope with this problem is to use Automatic Design Space Exploration (ADSE) techniques. We developed the Framework for Automatic Design Space Exploration (FADSE) which is focused on microarchitectural optimizations. This framework includes several state-of-the ar...

The paper presents a generalization of the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and its application in selected well-known twoand threeobjective optimization benchmark problems. The proposed solution is referred to as our SPEA3. The generalization consists in the exchange of the environmental selection procedure in SPEA2 for a new original algorithm which aims to determine the final...

We present variants of an ant colony optimization (MO-ACO) algorithm and of an evolutionary algorithm (SPEA2) for tackling multi-objective combinatorial optimization problems, hybridized with an iterative improvement algorithm and the Robust Tabu Search algorithm. The performance of the resulting hybrid stochastic local search (SLS) algorithms is experimentally investigated for the bi-objective...

This paper presents results of extensive computational experiments in which evolutionary multiobjective algorithms were used to find Pareto-optimal solutions to a complex structural design problem. In particular, Strength-Pareto Evolutionary Algorithm 2 (SPEA2) was combined with a mathematical programming method to find optimal designs of steel structural systems in tall buildings with respect ...

A new multi-objective evolutionary algorithm which can be applied to many nonlinear multi-objective optimization problems is proposed. Its aim is to obtain a discrete fixed size set approximating the complete Pareto-front quickly. It adapts ideas from different multiand single-objective optimization evolutionary algorithms, although it also incorporates new devices, namely, a new method to impr...

This article is concerned with the multitask multiagent allocation problem via many-objective optimization for systems (MASs). First, a novel layered MAS model constructed to address that includes both original task simplification and allocation. In first layer of model, deep Q-learning method introduced simplify prioritization set. second modified shift-based density estimation (MSDE) put forw...

One way to cope with a huge design space formed by several parameters is using methods for Automatic Design Space Exploration (ADSE). Recently we developed a Framework for Automatic Design Space Explorations focused on micro-architectural optimizations. In this article we evaluate the influence of three different evolutionary algorithms on the performance of design space explorations. More prec...

In this paper, a new genetic algorithm for multi-objective optimization problems is introduced. That is called ”Neighborhood Cultivation GA (NCGA)”. In the recent studies such as SPEA2 or NSGA-II, it is demonstrated that some mechanisms are important; the mechanisms of placement in an archive of the excellent solutions, sharing without parameters, assign of fitness, selection and reflection the...

Streptococcal pyrogenic exotoxin A (SPE-A) and SPE-B have been implicated in the pathogenesis of severe group A streptococcal (GAS) disease. We studied 31 invasive GAS strains including 18 isolates from patients with toxic shock syndrome and 22 noninvasive strains isolated in The Netherlands between 1994 and 1998. These strains were associated with the different allelic variants of the gene enc...