Many scientific applications running in Cloud Computing system are workflow applications that contains large number of tasks and in which tasks are connected by precedence relations. Efficient scheduling the workflow tasks become a challenging issue in Cloud Computing environments because the scheduling decides performance of the applications. Unfortunately, finding the optimal scheduling is kn...

Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to produce the phenomenon of stagnation and precocity. This paper introduces improve...

Ant colony optimization is a technique for optimization that was introduced in the early 1990’s. The inspiring source of ant colony optimization is the foraging behavior of real ant colonies. This behavior is exploited in artificial ant colonies for the search of approximate solutions to discrete optimization problems, to continuous optimization problems, and to important problems in telecommun...

This paper presents a comparative study of Ant Colony and Genetic Algorithms for VLSI circuit bi-partitioning. Ant colony optimization is an optimization method based on behaviour of social insects [27] whereas Genetic algorithm is an evolutionary optimization technique based on Darwinian Theory of natural evolution and its concept of survival of the fittest [19]. Both the methods are stochasti...

This paper presents a modification of the ant colony optimization algorithm (ACO) intended to introduce psychology factor of emotion into the algorithm. We define only two emotions ants could have, positive and negative, and correspond to two reaction to perception respectively. For avoiding premature convergence allows Emotional Ant Colony Optimization (EACO) to continue search for better even...

Multi Compartment Vehicle Routing Problem is an extension of the classical Capacitated Vehicle Routing Problem where different products are transported together in one vehicle with multiple compartments. Products are stored in different compartments because they cannot be mixed together due to differences in their individual characteristics. The problem is encountered in many industries such as...

For wireless sensor networks, the core issue is to design an energy-efficient network protocol as far as possible. Ant colony algorithm has proved to be effective in prolonging the network’s lifecycle and ensuring the reliability of data transmission. In conditions of network topology’s dynamic changes, we optimized the basic ant colony algorithm and introduced the pheromone broadcasting mechan...

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...

Set covering problem is the model for many important industrial applications. In this paper, we solve some benchmarks of this problem with ant colony optimization algorithms using a new transition rule. A look-ahead mechanism was incorporated to check constraint consistency in ant computing. Computational results are presented showing the advantages to use this additional mechanism to ant syste...

By use of the properties of ant colony algorithm and genetic algorithm, a novel ant colony genetic hybrid algorithm, whose framework of hybrid algorithm is genetic algorithm, is proposed to solve the traveling salesman problems. The selection operator is an artificial version of natural selection, and chromosomes with better length of tour have higher probabilities of being selected in the next...