this article presents the application of two algorithms: heuristic big bang-big crunch (hbb-bc) and a heuristic particle swarm ant colony optimization (hpsaco) to discrete optimization of reinforced concrete planar frames subject to combinations of gravity and lateral loads based on aci 318-08 code. the objective function is the total cost of the frame which includes the cost of concrete, formw...

Ant Colony Optimization (ACO) is a well-known swarm intelligence method, inspired in the social behavior of ant colonies for solving optimization problems. When facing large and complex problem instances, parallel computing techniques are usually applied to improve the efficiency, allowing ACO algorithms to achieve high quality results in reasonable execution times, even when tackling hard-to-s...

To build awareness of the development of ant colony optimization (ACO), this study clarifies the citation and bibliometric analysis of research publications of ACO during 1996–2010. This study analysed 12,960 citations from a total of 1372 articles dealing with ACO published in 517 journals based on the databases of SCIE, SSCI and AH&CI, retrieved via the Web of Science. Bradford Law and Lotka’...

In this paper the NP-hard single machine total weighted tardiness scheduling problem in presence of sequence-dependent setup times is faced with a new Ant Colony Optimization (ACO) approach. The proposed ACO algorithm is based on a new global pheromone update mechanism, which makes the pheromone trails asymptotically range between two bounds arbitrarily fixed and the ACO learning mechanism ind...

Considering the high costs of the implementation and maintenance of gas distribution networks in urban areas, optimal design of such networks is vital. Today, urban gas networks are implemented within a tree structure. These networks receive gas from City Gate Stations (CGS) and deliver it to the consumers. This study presents a comprehensive model based on Mixed Integer Nonlinear Programming (...

BACKGROUND The recognition of asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) as a distinct phenotype of COPD or asthma has increased. Although ACO has worse clinical features than non-ACO COPD, limited information is available on long-term outcomes of lung function decline for ACO and non-ACO COPD. METHODS COPD patients with at least 3 years of follow-up were selected from ...

The Ant Colony Optimization (ACO) algorithms are being applied successfully to a wide range of problems. ACO algorithms could be good alternatives to existing algorithms for hard combinatorial optimization problems (COPs). In this paper we investigate the influence of the probabilistic model in model-based search as ACO. We present the effect of four different probabilistic models for ACO algor...

In this paper Hybrid Ant Colony Optimization (HAntCO) approach in solving Multi–Skill Resource Constrained Project Scheduling Problem (MS–RCPSP) has been presented. We have proposed hybrid approach that links classical heuristic priority rules for project scheduling with Ant Colony Optimization (ACO). Furthermore, a novel approach for updating pheromone value has been proposed, based on both th...

Ant Colony Optimization (ACO) differs substantially from other meta-heuristics such as Evolutionary Algorithms (EA). Two of its distinctive features are: (i) it is constructive rather than based on iterative improvements, and (ii) it employs problem knowledge in the construction process via the heuristic function, which is essential for its success. In this paper, we introduce the ACO encoding,...

Creating accountable care organizations (ACOs) has been widely discussed as a strategy to control rapidly rising healthcare costs and improve quality of care; however, building an effective ACO is a complex process involving multiple stakeholders (payers, providers, patients) with their own interests. Also, implementation of an ACO is costly in terms of time and money. Immature design could cau...