Ant Colony Optimization (ACO) is a meta-heuristic that has been applied to a diverse set of optimization problems. Problems formulated using ACO have the beneficial quality that solutions are generally constructed making it possible to incorporate constraints during the construction process. Recently, problems in the telecommunications domain have utilized ACO heuristics for routing and fault l...

OBJECTIVE Analyze statistical risks facing CMS and Accountable Care Organizations (ACOs) under the Medicare Shared Savings Program (MSSP). METHODS We calculate the probability that shared savings formulas lead to inappropriate payment, payment denial, and/or financial penalties, assuming that ACOs generate real savings in Medicare spending ranging from 0-10%. We also calculate expected paymen...

In optimization problem, Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO) have been known as good alternative techniques. GA is designed by adopting the natural evolution process, while ACO is inspired by the foraging behaviour of ant species. This paper presents a hybrid GA-ACO for Travelling Salesman Problem (TSP), called Genetic Ant Colony Optimization (GACO). In this metho...

Ant Colony Optimization (ACO) is a metaheuristic that is inspired by the pheromone trail laying and following behavior of some ant species. Artificial ants in ACO are stochastic solution construction procedures that build candidate solutions for the problem instance under concern by exploiting (artificial) pheromone information that is adapted based on the ants’ search experience and possibly a...

In this paper we propose an ant colony optimization metaheuristic (ACO-CF) to solve the machine–part cell formation problem. ACO-CF is a MAX2MIN ant system, which is implemented in the hyper-cube framework to automatically scale the objective functions of machine–part cell formation problems. As an intensification strategy, we integrate an iteratively local search into ACO-CF. Based on the assi...

Biological inspired routing or bio-inspired routing is a new heuristic routing algorithm in wireless sensor network, which is inspired from biological activities of insects. ACO is ants’ inspired routing algorithm ACO, which has the ability to find shortest path and re-establish the new route in the case of route failure. In order to improve the network performance i.e. increase network lifetim...

A general-purpose, simulation-based algorithm S-ACO for solving stochastic combinatorial optimization problems by means of the ant colony optimization (ACO) paradigm is investigated. Whereas in a prior publication, theoretical convergence of S-ACO to the globally optimal solution has been demonstrated, the present article is concerned with an experimental study of S-ACO on two stochastic proble...

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 ...

IMPORTANCE Fostering accountability in the Medicare Accountable Care Organization (ACO) programs may be challenging because traditional Medicare beneficiaries have unrestricted choice of health care providers, are attributed to ACOs based on utilization, and often receive fragmented care. OBJECTIVE To measure 3 related constructs relevant to ACO incentives and their capacity to manage care: s...

This paper introduces one of the most profound Swarm Intelligence-based approaches, namely Ant Colony Optimization (ACO). The different operators in ACO and their effect on the quality of solution are briefly discussed. The ACO algorithms variants like Ant System (AS), Elitist Ant System (EAS), Rankbased Ant System (ASrank), Min-Max based Ant System (MMAS) are detailed. The paper puts forth a s...