This paper presents a comparison in the performance analysis between a newly developed mutation operator called Scaled Truncated Pareto Mutation (STPM) and an existing mutation operator called Log Logistic Mutation (LLM). STPM is used with Laplace Crossover (LX) taken from literature to form a new generational RCGA called LX-STPM. The performance of LX-STPM is compared with an existing RCGA cal...

Traditional Genetic Algorithms (GA) use crossover and mutation as the main genetic operators to achieve population diversity. Previous work using a biologically inspired genetic operator called transposition, allowed the GA to reach better solutions by replacing the traditional crossover operators. In this paper we extend that work to the case of asexual reproduction. The GA efficiency was comp...

In the GA approach the parameters that influence its performance include population size, crossover rate and mutation rate. Genetic algorithms are suitable for traversing large search spaces since they can do this relatively fast and because the mutation operator diverts the method away from local optima, which will tend to become more common as the search space increases in size. GA’s are base...

We empirically investigate the use of relocation operator as a local search operator, in combination with genetic search, in a Tree Adjoining Grammar Guided Genetic Programming system (TAG3P). The results show that, on all the problems we tried, the use of the relocation operator as a local search operator in TAG3P outperforms TAG3P using purely crossover and mutation, and also outperforms stan...

Crossover and mutation are two of the most important genetic operators found in genetic algorithms. There has been much debate as to which of these is practically and theoretically more effective. This literature review highlights the principal milestones of this debate. The conclusion we reach is that there is no evidence to show that either operator is better than the other, and that both ope...

real coded genetic algorithm, rcga, is the type of ga which operates on chromosomes with real valued parameters. different mutation and crossover operations are defined for rcga. one usable crossover for this kind of ga is to consider its chromosomes simply as bit strings and utilize the same operations as binary coded ga. in this paper, we attempt to show that this kind of crossover can not ha...

Evolutionary algorithms solve problems by simulating the evolution of a population candidate solutions. We focus on evolving permutations for ordering such as traveling salesperson problem (TSP), well assignment quadratic (QAP) and largest common subgraph (LCS). propose cycle mutation, new mutation operator whose inspiration is well-known crossover operator, concept permutation cycle. use fitne...

Multi-robot task allocation determines the task sequence and distribution for a group of robots in multi-robot systems, which is one of constrained combinatorial optimization problems and more complex in case of cooperative tasks because they introduce additional spatial and temporal constraints. To solve multi-robot task allocation problems with cooperative tasks efficiently, a subpopulation-b...

In the reverse logistics recycling process, considering diversity of types, a variety vehicle models are used to meet requirements. Therefore, this paper considers fixed costs, transportation carbon emission costs during driving, and time penalty in process under multiple constraints such as types windows center. The recovery point is model, an improved genetic algorithm solve it. Drawing lesso...

In this paper we present two sets of empirical data evaluating the performance of a new Cleanup operator for evolutionary approaches to the travelling salesman problem (TSP). For raw data we have used standard road mileage charts of the USA, Great Britain and Ireland, which enable us to generate a reference table with appropriate city to city distances. A wide variety of standard genetic parame...