Improved Genetic Algorithm to Optimization Pattern in Traffic Network Layout Problem

Autor:	Kang Zhou, Wenbo Dong, Yingying Duan, Qinhong Fu
Rok vydání:	2015
Předmět:	Competition strategy Core (game theory) Mathematical optimization Meta-optimization Phrase Computer science Genetic algorithm Improved algorithm Scale (descriptive set theory) Traffic network
Zdroj:	Communications in Computer and Information Science ISBN: 9783662490136 BIC-TA
DOI:	10.1007/978-3-662-49014-3_13
Popis:	The main core problem in optimization filed is to apply the optimization method devised by adopting a meta-heuristic algorithm to large-scale traffic network layout problem based on contribution center (TNLOSP). Improved Genetic Algorithm (IGA) is proposed to deal with this problem instead of traditional one. Two improvements are added to previous algorithm: Prim Stochastic Algorithm (PSA) and a fair competition strategy. In tuning phase, such core parameters in crossover rate, fairness coefficient \(p_{0}\), and the like as are synchronously optimized; In comparative analysis phrase, in large part as a consequence of comparison, the thesis focuses on a great deal of experimental analysis on determining more accurately some advantages of the algorithm. Showing though the experiment that improved algorithm has more advantages in efficiency and precision of solutions than traditional one by testing different scale populations. Therefore, proving that these improvements are of feasibility.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d88f996ecc86d2182cc25f5473974da3 https://doi.org/10.1007/978-3-662-49014-3_13 Zobrazit plný text záznamu