The quadratic assignment problem aims to find an optimal assignment of a set of facilities to a set of locations that minimizes an objective function depending on the flow between facilities and the distance between locations. In this paper we investigate a Genetic Algorithm (GA) using new crossover operators to guide the search towards unexplored regions of the search space. First we define a ...

In this talk, we will consider the effect of the optimized crossover within the framework of Genetic Algorithms (GAs) and look at some cases where this procedure is performed efficiently. The optimized crossover operator finds the best possible offspring (with respect to the solutions encoding) in a crossover, given two solutions of the parents. The well-known optimized crossover operator for t...

Exponential crossover in Differential Evolution (DE), which is similar to 1-point crossover in genetic algorithms, continues to be used today as a default crossover operator for DE. We demonstrate that exponential crossover exploits an unnatural feature of some widely used synthetic benchmarks such as the Rosenbrock function – dependencies between adjacent variables. We show that for standard D...

Inspired by evolutionary game theory, this paper modifies previous mixed strategy framework, adding a new mutation operator and extending to crossover operation, and proposes co-evolutionary algorithms based on mixed crossover and/or mutation strategy. The mixed mutation strategy set consists of Gaussian, Cauchy, Levy, single point and differential mutation operators; the mixed crossover strate...

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...

We extend a recently developed exact schema based, or coarse grained, formulation of genetic dynamics [12, 13, 14] and its associated exact Schema theorem to an arbitrary selection scheme and a general crossover operator. We show that the intuitive“building block” interpretation of the former is preserved leading to hierarchical formal solutions of the equations that upon iteration lead to new ...

Increasing of net energy storage (Q net) and discharge time of phase change material (t PCM), simultaneously, are important purpose in the design of solar systems. In the present paper, Multi-Objective (MO) based on hybrid of Particle Swarm Optimization (PSO) and multiple crossover and mutation operator is used for Pareto based optimization of solar systems. The conflicting objectives are Q net...

<p>Route planning is an important part of road network. To select optimized route several factors such as flow traffic, speed limits road. are concerned. Total cost a network depends on the number junctions between source and destination. Due to growth nodes in it becomes tough job determine exact path using deterministic algorithms so cases genetic (GA) plays vital role find route. Cross...

This paper investigates the use of more than one crossover operator to enhance the performance of genetic algorithms. Novel crossover operators are proposed such as the Collision crossover, which is based on the physical rules of elastic collision, in addition to proposing two selection strategies for the crossover operators, one of which is based on selecting the best crossover operator and th...

In this paper, a new multi-objective path-finding model is proposed to find optimal paths in road networks with time-dependent stochastic travel times. This study is motivated by the fact that different travelers usually have different route-choice preferences, often involving multiple conflicting criteria such as expected path travel time, variance of path travel time and so forth. However, mo...