In this work, we introduce a new method for the sensitivity analysis of model output in the presence of finite changes in one or more of the exogenous variables. We define sensitivity measures that do not rest on differentiability. We relate the sensitivity measures to classical differential and comparative statics indicators. We prove a result that allows us to obtain the sensitivity measures at the same cost of one-variable-at-a-time methods, thus making their estimation feasible also for computationally intensive models. We discuss in detail the derivation of managerial insights formulating a procedure based on the concept of "Settings". The method is applied to the sensitivity analysis of a discrete change in optimal order quantity following a jump in the exogenous variables of a nonlinear programming inventory model.
Sensitivity Analysis with Finite Changes: an Application to Modified EOQ Models
BORGONOVO, EMANUELE
2010
Abstract
In this work, we introduce a new method for the sensitivity analysis of model output in the presence of finite changes in one or more of the exogenous variables. We define sensitivity measures that do not rest on differentiability. We relate the sensitivity measures to classical differential and comparative statics indicators. We prove a result that allows us to obtain the sensitivity measures at the same cost of one-variable-at-a-time methods, thus making their estimation feasible also for computationally intensive models. We discuss in detail the derivation of managerial insights formulating a procedure based on the concept of "Settings". The method is applied to the sensitivity analysis of a discrete change in optimal order quantity following a jump in the exogenous variables of a nonlinear programming inventory model.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.