The purpose of this paper is to present a new hierarchic method based on swarm
intelligence algorithms for solving the well-known traveling salesman problem. The swarm …

Ant Colony Optimization (ACO) is a bioinspired metaheuristic based on ants foraging used
to solve different classes of problems. In this paper, we show how, using a Two-Stage …

Network topology discovery describes the physical structure of the network, which in turn
reflects the purpose of this network design. Used tools and techniques vary depending on …

This work investigates the effect of elite pool that has high-quality and diverse solutions in
three hybrid population-based meta-heuristics with an elite pool of a hybrid Elitist-Ant …

Ant colony optimization (ACO) is a metaheuristic approach for combinatorial optimization
problems. With the introduction of hypercube framework, invariance property of ACO …

This work investigates the effects achieved by using an adaptive elite pool over a basic
population-based approach, such as, the ant system approach, to different combinatorial …

The current work surveys 245 papers and research reports related to algorithms and
methods inspired from nature for solving supply chain and logistics optimization problems …

This work investigates the performance of a hybrid population-based meta-heuristic with an
external memory structure of a hybrid elitist-ant system (elitist-AS). This memory is known as …

旅行Agent 问题是一类复杂的组合优化问题, 目的在于解决移动Agent 在不同主机间移动如何
规划最优的迁移路线. 在蚁群算法的基础上, 引入变异运算, 并且对蚁群算法的全局和局部更新 …

This paper proposes a novel discrete bio-inspired chicken swarm optimization algorithm
(CSO) to solve the problem of the traveling salesman problem (TSP) which is one of the …