Convergence properties of simulated annealing for continuous global optimization

被引：34

作者：

Locatelli, M ^{[1
]}

机构：

[1] UNIV MILAN, DIPARTIMENTO SCI INFORMAZ, VIA COMELICO 39-41, I-20135 MILAN, ITALY

来源：

JOURNAL OF APPLIED PROBABILITY | 1996年 / 33卷 / 04期

关键词：

simulated annealing; continuous global optimization; cooling schedule;

D O I：

10.2307/3214991

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper conditions for the convergence of a class of simulated annealing algorithms for continuous global optimization are given. The previous literature about the subject gives results for the convergence of algorithms in which the next candidate point is generated according to a probability distribution whose support is the whole feasible set. A class of possible cooling schedules has been introduced in order to remove this restriction.

引用

页码：1127 / 1140

页数：14

共 19 条

[1]

ANILY S, 1985, PROBABILISTIC ANAL S

[2]

[Anonymous], P INT C COMP AID DES

[3] CONVERGENCE THEOREMS FOR A CLASS OF SIMULATED ANNEALING ALGORITHMS ON R(D) [J].