Showing 1 - 10 of 67
Persistent link: https://www.econbiz.de/10011090295
The aim of this paper is to quantify the benefit of demand and inventory smoothing in contrasting the extreme volatility and impetuous alteration of the market produced by the current economic recession. To do so we model a traditional supply chain and we test five settings of order smoothing...
Persistent link: https://www.econbiz.de/10011090318
AMS classifications; 05C50; 05E30;
Persistent link: https://www.econbiz.de/10011090354
AMS classifications: 05E30; 05B20
Persistent link: https://www.econbiz.de/10011090355
AMS classifications: 05C50, 05E99;
Persistent link: https://www.econbiz.de/10011090380
Abstract: Factor screening searches for the really important inputs (factors) among the many inputs that are changed in a realistic simulation experiment. Sequential bifurcation (SB) is a sequential method that changes groups of inputs simultaneously. SB is the most efficient and effective...
Persistent link: https://www.econbiz.de/10011090433
This article illustrates simulation optimization through an (s, S) inventory management system.In this system, the goal function to be minimized is the expected value of specific inventory costs.Moreover, specific constraints must be satisfied for some random simulation responses, namely the...
Persistent link: https://www.econbiz.de/10011090482
Classic linear regression models and their concomitant statistical designs assume a univariate response and white noise.By definition, white noise is normally, independently, and identically distributed with zero mean.This survey tries to answer the following questions: (i) How realistic are...
Persistent link: https://www.econbiz.de/10011090588
This article reviews so-called screening in simulation; i.e., it examines the search for the really important factors in experiments with simulation models that have very many factors (or inputs). The article focuses on a most efficient and effec- tive screening method, namely Sequential...
Persistent link: https://www.econbiz.de/10011090683
Design Of Experiments (DOE) is needed for experiments with real-life systems, and with either deterministic or random simulation models. This contribution discusses the different types of DOE for these three domains, but focusses on random simulation. DOE may have two goals: sensitivity analysis...
Persistent link: https://www.econbiz.de/10011090795