A Brief Overview of Physics-inspired Metaheuristic Optimization Techniques

利用元启发式优化实现可持续非同向并行机调度的一般框架：简要概述

A general Framework for Utilizing Metaheuristic Optimization for Sustainable Unrelated Parallel Machine Scheduling: A concise overview

本文从可持续发展目标视角，探讨了遗传算法等元启发式优化方法在解决非同向并行机调度问题（UPMSP）中的应用，评估其在提升资源利用、降低能耗和环境影响等方面的有效性。

Evolution of Ant Colony Optimization Algorithm -- A Brief Literature Review

Ant Colony Optimization (ACO) is a metaheuristic proposed by Marco Dorigo in 1991 based on behavior of biological ants. Pheromone laying and selection of shortest route with the help of pheromone inspired development of first ACO algorithm. Since, presentation of first such algorithm, many researchers have worked and published their research in this field. Though initial results were not so promising but recent developments have made this metaheuristic a significant algorithm in Swarm Intelligence. This research presents a brief overview of recent developments carried out in ACO algorithms in …

通过基于对立的学习提升元启发式算法在高层建筑控制系统最优定位中的效率

Boosting the Efficiency of Metaheuristics Through Opposition-Based Learning in Optimum Locating of Control Systems in Tall Buildings

本文综述对立学习在元启发式优化中的应用，通过高层建筑MR阻尼器控制系统定位案例，证明其能显著提升优化质量与速度。

Firefly Algorithm: Recent Advances and Applications

Nature-inspired metaheuristic algorithms, especially those based on swarm intelligence, have attracted much attention in the last ten years. Firefly algorithm appeared in about five years ago, its literature has expanded dramatically with diverse applications. In this paper, we will briefly review the fundamentals of firefly algorithm together with a selection of recent publications. Then, we discuss the optimality associated with balancing exploration and exploitation, which is essential for all metaheuristic algorithms. By comparing with intermittent search strategy, we conclude that metaheu…

Neural Networks for Dynamic Shortest Path Routing Problems - A Survey

This paper reviews the overview of the dynamic shortest path routing problem and the various neural networks to solve it. Different shortest path optimization problems can be solved by using various neural networks algorithms. The routing in packet switched multi-hop networks can be described as a classical combinatorial optimization problem i.e. a shortest path routing problem in graphs. The survey shows that the neural networks are the best candidates for the optimization of dynamic shortest path routing problems due to their fastness in computation comparing to other softcomputing and metah…

优化中的自然启发式算法：介绍、混合与见解

Nature-Inspired Algorithms in Optimization: Introduction, Hybridization and Insights

本章概述了优化问题及自然启发式元启发式算法，探讨了算法混合的作用与相关问题，并强调了基准测试在评估优化算法性能中的重要性。