智能计算机与应用
智能計算機與應用
지능계산궤여응용
Intelligent Computer and Applications
2015年
5期
59-64
,共6页
彭乔姿%卢宇婷%林禹攸%王颖喆
彭喬姿%盧宇婷%林禹攸%王穎喆
팽교자%로우정%림우유%왕영철
模拟退火算法%新解产生方式%温度函数%Sobol’g函数%碎纸片拼接问题
模擬退火算法%新解產生方式%溫度函數%Sobol’g函數%碎紙片拼接問題
모의퇴화산법%신해산생방식%온도함수%Sobol’g함수%쇄지편병접문제
Simulated Annealing Algorithm%Production of New Solutions%Temperature Function%Sobol’ g Function%Res-toration of the Shredded Psaper
简单介绍了传统模拟退火算法的流程、算法所涉及的重要参数、当下模拟退火算法改进的主要改进角度以及一种已有的改进算法———加温退火法。提出了一类基于改进新解产生方式及温度函数的模拟退火算法,一共包含四种新的改进算法,命名为:多粒子寻优模拟退火算法、混合温度模拟退火算法、混合多粒子寻优模拟退火算法、加温多粒子寻优模拟退火算法。最后分别将这四种改进算法应用于求解Sobol’ g函数最小值和碎纸片拼接问题。实验证明改进后的算法是有效的,分别在解的质量以及算法效率上有所提升。
簡單介紹瞭傳統模擬退火算法的流程、算法所涉及的重要參數、噹下模擬退火算法改進的主要改進角度以及一種已有的改進算法———加溫退火法。提齣瞭一類基于改進新解產生方式及溫度函數的模擬退火算法,一共包含四種新的改進算法,命名為:多粒子尋優模擬退火算法、混閤溫度模擬退火算法、混閤多粒子尋優模擬退火算法、加溫多粒子尋優模擬退火算法。最後分彆將這四種改進算法應用于求解Sobol’ g函數最小值和碎紙片拼接問題。實驗證明改進後的算法是有效的,分彆在解的質量以及算法效率上有所提升。
간단개소료전통모의퇴화산법적류정、산법소섭급적중요삼수、당하모의퇴화산법개진적주요개진각도이급일충이유적개진산법———가온퇴화법。제출료일류기우개진신해산생방식급온도함수적모의퇴화산법,일공포함사충신적개진산법,명명위:다입자심우모의퇴화산법、혼합온도모의퇴화산법、혼합다입자심우모의퇴화산법、가온다입자심우모의퇴화산법。최후분별장저사충개진산법응용우구해Sobol’ g함수최소치화쇄지편병접문제。실험증명개진후적산법시유효적,분별재해적질량이급산법효솔상유소제승。
The paper simply introduces the traditional simulated annealing algorithm through its process, key parameters, main aspects of improvement of the algorithm at present, and a new improvement named Simulated Annealing Algorithm with Heating Process which was put forward by other scholars.Then the paper puts forward a new type of simulated annea-ling algorithm based on improving production of new solutions and temperature function, including four improved algorithms which are named Multi-objectives Optimization Simulated Annealing Algorithm, Combined Temperature Simulated Annea-ling Algorithm, Combined Multi-objectives Optimization Simulated Annealing Algorithm and Multi-objectives Optimiza-tion Simulated Annealing Algorithm with Heating Process respectively.At last, the paper applies these four improved algo-rithms to determine the minimum value of Sobol’ g function and restore the shredded paper respectively.The experiments demonstrate that the new type of simulated annealing algorithm is effective and show the improvement of both the solutions of those two problems and algorithm’ s efficiency.