Discrete optimization with estimation

Author

Yan, Di ; Mukai, Hiroaki

Author_Institution

Dept. of Syst. Sci. & Math., Washington Univ., St. Louis, MO, USA

fYear

1989

fDate

13-15 Dec 1989

Firstpage

2463

Abstract

A computational method is proposed for finding a global solution to the discrete optimization problem in which the objective function must be estimated by Monte Carlo simulation. The proposed method is very simple, requiring mainly a computer program for simulating the system and evaluating its performance, yet it can be shown to find a global optimum solution. The method should be practical, since it can be easily used in conjunction with heuristics and yet retain its global convergence property. The Markov chain generated by the method is analyzed. It is shown under mild conditions that the probability that the current solution estimate is globally optimum converges to one. The method is expected to find many practical applications in the fields of manufacturing engineering, traffic engineering, operations research, and management science

Keywords

Markov processes; Monte Carlo methods; convergence of numerical methods; optimisation; Markov chain; Monte Carlo simulation; discrete optimization; global convergence; objective function; Computational modeling; Computer aided manufacturing; Computer simulation; Credit cards; Engineering management; Manufacturing processes; Operations research; Random number generation; Stochastic processes; Telephony;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1989., Proceedings of the 28th IEEE Conference on

Conference_Location

Tampa, FL

Type

conf

DOI

10.1109/CDC.1989.70620

Filename

70620