In this paper, we introduce and study a generalized Yosida approximation operator associated to H(·, ·)-co-accretive operator and discuss some of its properties. Using the concept of graph convergence and resolvent operator, we establish the convergence for generalized Yosida approximation operator. Also, we show an equivalence between graph convergence for H(·, ·)-co-accretive operator and gen...

in this paper, we introduce and study the concept of $r$-fuzzy regular semi open (closed) sets in smooth topological spaces. by using $r$-fuzzy regular semi open (closed) sets, we define a new fuzzy closure operator namely $r$-fuzzy regular semi interior (closure) operator. also, we introduce fuzzy regular semi continuous and fuzzy regular semi irresolute mappings. moreover, we investigate the ...

Abstract In order to solve the problems such as poor diversity and convergence ability of offspring population NSGA-II Algorithm in vehicle production scheduling problem, an improved shop algorithm based on is proposed. The NSGA-ii mainly focuses crossover mutation traditional Algorithm, proposes a new self-adaptive Crossover operator. By comparing individual crowding degree with average popula...

In this paper, we present a study of the use of an artificial immune system (CLONALG) for solving constrained global optimization problems. As part of this study, we evaluate the performance of the algorithm both with binary encoding and with real-numbers encoding. Additionally, we also evaluate the impact of the mutation operator in the performance of the approach by comparing Cauchy and Gauss...

This paper proposes a generalized Hybrid Real-coded Quantum Evolutionary Algorithm (HRCQEA) for optimizing complex functions as well as combinatorial optimization. The main idea of HRCQEA is to devise a new technique for mutation and crossover operators. Using the evolutionary equation of PSO a Single-Multiple gene Mutation (SMM) is designed and the concept of Arithmetic Crossover (AC) is used ...

This paper identifies the limitations of conventional crossover in genetic algorithms when operating on two chromosomes of differing lengths. To address these problems, the concept of a Semantic Hierarchy (i.e. tree of meaning) of a genotype within a genetic algorithm is introduced. With this in mind, a new form of crossover operator known as Hierarchical Crossover is presented, capable of perf...

Crossover is an important genetic operation that helps in random recombination of structured information to locate new points in the search space, in order to achieve a good solution to an optimization problem. The conventional crossover operation when applied on a pair of binary strings will usually not retain the total number of 1’s in the offsprings to be the same as that of their parents. B...

Colliding Bodies Optimization (CBO) is a population-based metaheuristic algorithm that complies physics laws of momentum and energy. Due to the stagnation susceptibility of CBO by premature convergence and falling into local optima, some meritorious methodologies based on Sine Cosine Algorithm and a mutation operator were considered to mitigate the shortcomings mentioned earlier. Sine Cosine Al...

Since crossover operator plays a vital role in genetic algorithms (GAs), several crossover operators have been proposed for the travelling salesman problem, which are then modified for the quadratic assignment problem (QAP). In this paper, we modify the sequential constructive crossover (SCX) operator for a simple GA to find heuristic solution to the QAP. Efficiency of the proposed GA using SCX...

Genetic algorithms (GAs) represent a method that mimics the process of natural evolution in effort to find good solutions. In that process, crossover operator plays an important role. To comprehend the genetic algorithms as a whole, it is necessary to understand the role of a crossover operator. Today, there are a number of different crossover operators that can be used in binary-coded GAs. How...