One of the challenges mutation testing is fixing faults. In debugging phase, all live mutants were repaired. Programs need high scores to be declared reliable program codes. Each test can allow identification multiple mutants. This what confuses faults process. The objective this research get shortest route so that it help in sorting mutant types during application improvement after testing. op...

The Learnable Ant Colony Optimization (LACO) is proposed to satellite ground station system scheduling problems. The LACO employs an integrated modelling idea which combines the ant colony model with the knowledge model. In order to improve the performance, LACO largely pursues the complementary advantages of ant colony model and knowledge model. Experimental results suggest that LACO is a feas...

Hybrid algorithm is proposed to solve combinatorial optimization problem by using Ant Colony and Genetic programming algorithms. Evolutionary process of Ant Colony Optimization algorithm adapts genetic operations to enhance ant movement towards solution state. The algorithm converges to the optimal final solution, by accumulating the most effective sub-solutions.

This paper presents an ant colony optimization based algorithm to solve real parameter optimization problems. In the proposed method, an operation similar to the crossover of the genetic algorithm is introduced into the ant colony optimization. The crossover operation with Laplace distribution following a few promising descent directions (FPDD-LX) is proposed to be performed on the pheromone of...

In this paper we try to introduce the Ant Colony Optimization (ACO) and its application in Economic Dispatch ED). In the step one we present theory and performance of ant colony and its history and its application in various applications and how work the ant colony algorithm. In step two we present ant colony optimization include Basic Concept, Ant Searching Behavior, Path Retracing and Pheromo...

In an emergency situation (e.g., tsunami, chemical spill, fire) it may be necessary to displace people to safer locations. Evacuation plans must be prepared so that these movements are properly organized. Based on the ACO (ant colony optimization) meta-heuristic we design a computational model to optimize a multi-objective path-finding associated to an evacuation planning problem. The results a...

Ant systems are flexible to implement and give possibility to scale because they are based on multi agent cooperation. The aim of this publication is to show the universal character of that solution and potentiality in implementing it in wide areas of applications. The increase of demand for effective methods of large document collections management is a sufficient stimulus to place the researc...

Due to the inventions in technology, Wireless sensor networks have been growing rapidly. Sensor nodes are capable of performing some processing, gathering required information and communicating with other connected nodes in the network. Sensor nodes are of limited energy which is a drawback during peak times in a network. Always energy is of primary concern in a wireless sensor networks. There ...

In this paper we analyze the application of the Ant Colony Optimization to the Minimum Weight Vertex Covering Problem. We use the software system that we developed and implemented different standard ACO algorithms to this problem: Ant Colony System, the use of Elitism, Rank based approach and the MinMax system. We have made a comparative assessment of the effectiveness of these algorithms to th...

Ant colony algorithms are computational methods for solving problems that are inspired by the behaviour of real ant colonies. One particularly interesting aspect of the behaviour of ant colonies is that relatively simple individuals perform complicated tasks. Examples for such collective behavior are: i) the foraging behaviour that guides ants on short paths to their food sources, ii) the colle...