The edge-set encoding is a direct tree encoding which applies search operators directly to trees represented as sets of edges. There are two variants of crossover operators for the edge-set encoding: With heuristics that consider the weights of the edges, or without heuristics. Due to a strong bias of the heuristic crossover operator towards the minimum spanning tree (MST) a population of solut...

Facility Layout Problem (FLP) is logic based combinatorial optimization problem. It is a meta-heuristic solution approach that gained significant attention to obtained optimal facility layout. This paper examines the convergence analysis by changing the crossover and mutation probability in an optimal facility layout. This algorithm is based on appropriate techniques that include multipoint swa...

The protein structure prediction problem is concerned with predicting the three dimensional native conformation of a protein from the corresponding one dimensional sequence of amino acids. This paper is concerned with solving the protein structure prediction problem on the simple HP lattice model of a protein. Many algorithms and search techniques exist in literature for solving the protein str...

In the framework of nonlinear systems identification by means of multiobjective genetic programming, the paper introduces a customized crossover operator, guided by fuzzy controlled regressor encapsulation. The approach is aimed at achieving a balance between exploration and exploitation by protecting well adapted subtrees from division during recombination. To reveal the benefits of the sugges...

In this paper we propose a robust genetic algorithm for the multi-mode resourceconstrained project scheduling problem. We present a new representation for the solutions to this problem, which includes an additional bit indicating the scheduling scheme used to construct the schedule, forward or backward. Moreover, we have developed new genetic operators which operate over this representation, ex...

In information retrieval research; Genetic Algorithms (GA) can be used to find global solutions in many difficult problems. This study used different similarity measures (Dice, Inner Product) in the VSM, for each similarity measure we compared ten different GA approaches based on different fitness functions, different mutations and different crossover strategies to find the best strategy and fi...

There is great interest for the development of semantic genetic operators to improve the performance of genetic programming. Semantic genetic operators have traditionally been developed employing experimentally or theoretically-based approaches. Our current work proposes a novel semantic crossover developed amid the two traditional approaches. Our proposed semantic crossover operator is based o...

This paper presents the results of an investigation, and optimization of scheduling system in Sohar University (as a case study) using the genetic algorithm (GA). GA techniques are useful for solving real-world scheduling problem such as timetable which is a complex work and usually done manually. This work focuses on scheduling courses timetable to allocate events (time, subject, and lecturer)...

This paper analyses the behavior of the crossover operator in a hardware implementation of Genetic Programming using Field Programmable Gate Arrays. Three different crossover operators that limit the lengths of programs are analysed: A truncating operator, a limiting operator that constrains the lengths of both offspring and a limiting operator that only constrains the length of one offspring. ...

The Crossover operator is common to most implementations of Genetic Programming (GP). Another, usually unavoidable, factor is some form of restriction on the size of trees in the GP population. This paper concentrates on the interaction between the Crossover operator and a restriction on tree depth demonstrated by the MAX problem , which involves returning the largest possible value for given f...