Although GAS are widely used for optimization problems and have obtained many good results, these are also holding problems, such as premature convergence problems and evolutionary stagnation problems. In this papel; the premature convergence caused by reduction of the diversity and evolutionary stagnation in GAS are observed, and a new genetic algorithm, named multi-step GA(MSGA) is proposed. ...

Premature convergence is a serious problem in many applications of evolutionary algorithms (EAs), since it decreases the EA’s chance to reach new high-quality regions of the search space and hence degrades the overall performance. In particular decoder-based EAs are frequently susceptible to premature convergence due to their encoding redundancy. Our comparison of four decoder-based EAs for the...

Genetic algorithms (GAs) have been applied to many difficult optimization problems such as track assignment and hypothesis managements for multisensor integration and data fusion. However, premature convergence has been a main problem for GAs. In order to prevent premature convergence, we introduce an allied strategy based on biological evolution and present a parallel Genetic Algorithm with th...

The applications of Clonal Selection Algorithms (CSAs) in solving combinatorial problems are frequently faced with a premature convergence problem and the maturation processes are trapped into a local optimum. This premature convergence problem occurs when the population of a clonal selection algorithm reaches a suboptimal state that the immune operators can no longer produce new immune cells w...

The problem of Dynamic Job Shop (DJS) scheduling is one of the most complex problems of machine scheduling. This problem is one of NP-Hard problems for solving which numerous heuristic and metaheuristic methods have so far been presented. Genetic Algorithms (GA) are one of these methods which are successfully applied to these problems. In these approaches, of course, better quality of solutions...

We present a new hypothesis concerning cognitive reflection and the relationship between System 1 and System 2, corresponding roughly to intuition and reason. This hypothesis postulates a tighter integration between systems than is implied by the common framework of separate modules. If systems are tightly coupled, as we propose here, an explanation of cognitive reflection may rest in the prema...

The definition of the hardness of a problem for GA’s has been tackled, eventually leading to the notion of deception [Gol89, HG94, Dav87]. It has been known for a while that the hardness of a problem is inherently related to the representation that is used. This fact will be illustrated below by showing that an easy problem (1’s counting problem) can become nearly unsolvable after a change of r...

Teachers and students have established social roles, norms and conventions when they encounter Computer-Supported Collaborative Learning (CSCL) systems in the classroom. Authority, a major force in the classroom, gives certain people, objects, representations or ideas the power to affect thought and behavior and influences communication and interaction. Effective computer-supported collaborativ...

The optimum of numerical problems quite often lies on the constraint boundary or even in a vertex of the feasible search space. In such cases the evolutionary algorithm (EA) frequently suffers from premature convergence because of a low success probability near the constraint boundaries. We analyze premature fitness stagnation and the success rates experimentally for an EA using self-adaptive s...