Quadratic assignment problem (QAP) is one of fundamental combinatorial optimization problems in many fields. Many real world applications such as backboard wiring, typewriter keyboard design and scheduling can be formulated as QAPs. Ant colony algorithm is a multi-agent system inspired by behaviors of real ant colonies to solve optimization problems. Ant colony optimization (ACO) is one of new ...

Ant colony optimization (ACO) is a metaheuristic for solving combinatorial optimization problems that is based on the foraging behavior of biological ant colonies. Starting with the 1996 seminal paper by Dorigo, Maniezzo and Colorni, ACO techniques have been used to solve the traveling salesperson problem (TSP). In this paper, we focus on a particular type of the ACO algorithm, namely, the rank...

Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when stagnation behaviour is avoided. Several approaches have been integrated with ACO to improve its performance for DOPs. The adaptation capabilities of ACO rely on the pheromone evaporation mechanism, where the rate is usually fixed. Pheromone evaporation may eliminate pheromone t...

The computational complexity of ant colony optimization (ACO) is a new and rapidly growing research area. The finite-time dynamics of ACO algorithms is assessed with mathematical rigor using bounds on the (expected) time until an ACO algorithm finds a global optimum. We review previous results in this area and introduce the reader into common analysis methods. These techniques are then applied ...

Increasingly complex urban traffic conditions often challenge the express services with long delivery path and much more time as consumed. In this paper, a Traffic Impact Factor (TIF) is introduced to model the impact of urban traffic conditions on express services. Based on the TIF, an optimization model is constructed to minimize the delivery distance and the time consumed. In the solution , ...

To make robot avoid obstacles in 3D space, the Pheromone of Ant Colony Optimization (ACO) in Fuzzy Control Updating is put forward, the Pheromone Updating value varies with The number of iterations and the path-planning length by each ant . the improved Transition Probability Function is also proposed, which makes more sense for each ant choosing next feasible point .This paper firstly, describ...

This paper sets up an Artificial Bee Colony (ABC) algorithm for evolving ant direction Ant Colony Optimization (ACO) to solve the Economic Power Dispatch (EPD) problem. The method ABC-ACO employs the bee colony to find a suitable and the best values operators to improve the ACO. The feasibility of the proposed approach was tested on IEEE 57-bus system. The proposed approach simulation results, ...

we propose a novel hybrid algorithm named ACO-FA, which integrates the merits of ant colony optimization (ACO) with firefly algorithm (FA) to solve unconstrained optimization problems. The main feature of the hybrid algorithm is to hybridize the solution construction mechanism of the ACO with the FA. In our hybrid algorithm, the initial solutions are generated randomly from the search space, an...

AIM To investigate change in the area of anterior capsular opening (ACO) after cataract surgery and its relation to the degree of postoperative anterior inflammation in patients with diabetes mellitus (DM). METHODS 31 eyes of 31 patients with DM and 30 eyes of 30 normal controls scheduled to undergo cataract surgery were examined prospectively. The area of ACO was measured with an anterior ey...

Aconitine (ACO) is well-known for causing lethal ventricular tachyarrhythmias. While cardiac Na+ channel opening during repolarization has long been documented in animal cardiac myocytes, the cellular effects and mechanism of ACO in human remain unexplored. This study aimed to assess the proarrhythmic effects of ACO in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). ACO ...