As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Due to the complex structure of modern systems, large-scale optimization has become the hot spot of practical engineering problems. An improved fireworks algorithm (FWA) is proposed to obtain the global optimal solution of large-scale optimization problems in a fast manner. To promote the ability to jump out of the local optimal solution, a differential sparks generation mechanism and a novel reinitialization mechanism are developed. To speed up the convergence, a dual-channel selection mechanism is proposed, in which an exclusive channel is given for differential sparks. The combination of differential sparks generation and dual-channel selection promotes the usage of known information, balances the diversity and convergence of the fireworks. Typical test suites and unmanned aerial vehicle (UAV) path planning are used to test the effectiveness and efficiency of the proposed algorithm. Simulation results demonstrate that the proposed algorithm can search for the global optimal solution in a large variable space and can obtain a short-distance path for the UAV.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.