Ant colony optimization (ACO) and its variants are applied extensively to resolve various continuous optimization problems. As per the various diversification and intensification schemes of ACO for continuous function optimization, researchers generally consider components of multidimensional state space to generate the new search point(s). However, diversifying to a new search space by updatin...

An efficient method for the cleavage of the p-methoxybenzyl protecting group of several alcohols in the presence of 0.5 equiv of trifluoromethanesulfonic acid and 1,3-dimethoxybenzene in dichloromethane at room temperature is described. 2011 Elsevier Ltd. All rights reserved. O OAc Me HO PMBO O-allyl 1 O AcO AcO NPhth AcO O NH CCl3 2 O OAc Me O O AcO AcO AcO

To overcome shortcomings when the ant colony optimization clustering algorithm (ACOC) deal with problem, this paper introduces a novel chaos. The main idea of is to apply chaotic mapping function in two stages optimization: pheromone initialization and update. application phase can encourage ants be distributed as many different initial states possible. Applying update stage add disturbance fac...

A novel version of Ant Colony Optimization (ACO) algorithms for solving continuous space problems is presented in this paper. The basic structure and concepts of the originally reported ACO are preserved and adaptation of the algorithm to the case of continuous space is implemented within the general framework. The stigmergic communication is simulated through considering certain direction vect...

Combining ant colony optimization (ACO) and multiobjective evolutionary algorithm based on decomposition (MOEA/D), this paper proposes a multiobjective evolutionary algorithm, MOEA/D-ACO. Following other MOEA/D-like algorithms, MOEA/D-ACO decomposes an multiobjective optimization problem into a number of single objective optimization problems. Each ant (i.e. agent) is responsible for solving on...