This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterparts as well as the AC...

Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when stagnation behaviour is addressed. Usually, permutation-encoded DOPs, e.g., dynamic travelling salesman problems, are addressed using ACO algorithms whereas binary-encoded DOPs, e.g., dynamic knapsack problems, are tackled by evolutionary algorithms (EAs). This is because of the...

Two flavonoid-deficient mutants, designated as fldL-1 and fldL-2, were isolated in EMS-mutagenized (0.15%, 10 h) M(2) progeny of grass pea (Lathyrus sativus L.). Both the mutants contained total leaf flavonoid content only 20% of their mother varieties. Genetic analysis revealed monogenic recessive inheritance of the trait, controlled by two different nonallelic loci. The two mutants differed s...

This brief updates Brief No. 2014-3 and explains changes in the Centers for Medicare & Medicaid Services (CMS) Accountable Care Organization (ACO) regulations issued in June 2015 pertaining to beneficiary assignment for Medicare Shared Savings Program ACOs. Overall, the regulatory changes are intended to (1) encourage ACOs to participate in two-sided risk contracts, (2) increase the likelihood ...

—The implementation methods of the tasks assignment and tasks scheduling for Wireless Sensor and Actuator Network (WSAN) are proposed in this paper. Firstly, the distributed auction algorithm was used to assign tasks to the optimal actuators. Secondly, the Ant Colony Optimization (ACO) algorithm whose parameters were optimized by Particle Swarm Optimization algorithm (PSO) was proposed for the...

background : cardiac arrest is a condition in which the heart is completely stopped and is not pumping any blood. although most cardiac arrest cases are reported from homes or hospitals, about 20% occur in public areas. therefore, these areas need to be investigated in terms of cardiac arrest incidence so that places of high incidence can be identi-fied and cardiac rehabilitation defibrillators...

This research merges the hierarchical reinforcement learning (HRL) domain and the ant colony optimization (ACO) domain. The merger produces a HRL ACO algorithm capable of generating solutions for both domains. This research also provides two specific implementations of the new algorithm: the first a modification to Dietterich’s MAXQ-Q HRL algorithm, the second a hierarchical ACO algorithm. Thes...

Ant Colony Optimization (ACO) algorithms construct solutions each time starting from scratch, that is, from an empty solution. Similar to ACO, Iterated Greedy is a constructive stochastic local search (SLS) method. However, differently from ACO, Iterated Greedy starts the solution construction from partial solutions. In this paper we examine the performance of a variation of MAX–MIN Ant System,...