Historical disaster events are taken as a case for space-correlation analysis, three-dimensional disasters space-time network are modeled and chain relationship of disaster nodes are mined by looking for similar space vector in network. Then transformed the vector discover problem into a path optimization problem and solved by using ant colony algorithm, where the pheromone parameter in the pro...

Ant colony optimization has been one of the most promising meta-heuristics since its appearance in early 1990s but it is specialized in discrete space optimization problems. To explore the utility of ACO in the filed of continuous problems, this paper proposes an orthogonal search embedded ACO (OSEACO) algorithm. By generating some grids in the search space and embedding an orthogonal search sc...

In this paper we present a multi-caste ant colony optimization approach, where each caste has its own set of parameters. Two variants are proposed: in the first, the composition of the castes remains fixed throughout the optimization, whilst the other allows ants to move from one caste to another. Results obtained in several traveling salesperson problem instances reveal that the adoption of a ...

This paper proposes a framework named multiobjective ant colony optimization based on decomposition (MoACO/D) to solve bi-objective traveling salesman problems (bTSPs). In the framework, a bTSP is first decomposed into a number of scalar optimization subproblems using Tchebycheff approach. To suit for decomposition, an ant colony is divided into many subcolonies in an overlapped manner, each of...

This paper proposes a stochastic optimization method, based on ant colony optimization, for the optimal choice of transformer sizes to be installed in a distribution network. This method is properly introduced to the solution of the optimal transformer sizing problem, taking into account the constraints imposed by the load the transformer serves throughout its life time and the possible transfo...

This paper shows how the presence of states in test objects can hinder or render impossible the search for test data using evolutionary testing. Additional guidance is required to find sequences of inputs that put the test object into some necessary state for certain test goals to become feasible. It is shown that data dependency analysis can be used to identify program statements responsible f...

Formulation of energy efficient protocols is of utmost importance for wireless sensor networks because of energy constraints of sensor nodes. When a number of nodes is deployed in a field located away from the base station, the nodes undergo unequal energy dissipation while transmitting information to the base station primarily due to two reasons: i) the difference in the distances of nodes fro...

The aggregation of individuals into colonies raises important questions about scaling of structure and function. We model the metabolic benefits and costs of two-dimensional, fractallike foraging trails, such as those used by ant colonies. Total area foraged by the colony and, consequently, resource flow to the nest and rate of colony metabolism, increase non-linearly with number of foragers (F...

Fuzzy logic has been a useful tool for modeling complex problems, with the use of fuzzy variables and fuzzy rules, and in this paper we use a fuzzy system for parameter adaptation in the Ant Colony Optimization (ACO metaheuristic). In this case we perform the dynamic adaptation of Alpha and Rho parameters; this is to control the abilities of ACO to perform a global and local search. Simulation ...

Traditional method of test paper generation is time-consuming, low efficient and low success. In order to improve the success rate of test paper, the paper puts forward an ant colony algorithm of automatic sets method. First, a mathematical model of constraint is built according to the requires of papers, and by using the ant colony algorithm, the optimal solution of grouping is obtained. Simul...