Freezing the Master Production Schedule Under Demand Uncertainty

Abstract

A substantial amount of behavioral research in business has attempted to uncover the relative importance decision makers attach to different decision variables (cues) used in their decision processes. This paper reports on two experiments that examine methodological issues concerning the assessment of cue importance. The first experiment examined whether the categorical descriptions given to cues in many modeling studies affect the importance decision makers attach to those cues. Results revealed that the importance attributed was significantly affected by the categories used to define cues. Additionally, because different techniques have been utilized to model cue importance, the second experiment examined the level of agreement between importance measures derived from two commonly used modeling techniques (ANOVA and information boards) under varying levels of task complexity. Results indicated that cue importance measures generally exhibited a moderate level of agreement. However, the use of different modeling techniques appears to affect the importance attributed to cues for some decision makers. In addition, the level of agreement was not affected by changes in task complexity. Implications of these results for future research studies that model decision behavior are discussed.

Freezing the master production schedule under single resource constraint and demand uncertainty

“…Therefore, neither the introduction of the demand uncertainty nor the capacity constraint changes the relative performance of PH according to schedule instability. However, the relative total cost performance of PH under capacity constraint and demand uncertainty observed in this study is quite different from that under demand uncertainty without considering capacity constraint observed by Sridharan and Berry (1990a). While a longer planning horizon reduces total cost under capacity constraint, it increases total cost when no capacity constraint is considered.…”

“…They also compared the relative importance of the MPS freezing parameters in influencing the total cost and schedule instability of the system. Sridharan and Berry (1990a), LaForge (1990, 1994), Lin and Krajewski (1992) extended the studies by Sridharan et al (1987Sridharan et al ( , 1988 from the case of deterministic demand to the case of demand uncertainty by introducing forecasting errors into the system. Lee (1993, 1996) and Zhao and Lam (1997) extended the studies by Sridharan et al (1987Sridharan et al ( , 1988) from single-level systems to multilevel MRP systems and found that some findings in single-level systems cannot be generalised to multi-level systems.…”

“…The other is to use a forecasting model to make forecast based on previous demands. The first approach was used by Lee and Adam (1986), Sridharan and Berry (1990a) and LaForge (1990, 1994), etc., while the second approach was used by Zhao and Lee (1993) and Zhao et al (1995), etc. This study will adapt the second approach and uses the moving average model to forecast future demands based on previous demands.…”

Impact of forecasting error on the performance of capacitated multi-item production systems

“…They also compared the relative importance of the MPS freezing parameters in influencing the total cost and SI of the system. Lin and Krajewski (1992), Sridharan and Berry (1990a) and LaForge (1990, 1994) extended the studies by Sridharan et al (1987Sridharan et al ( , 1988 from the case of deterministic demand to the case of demand uncertainty by introducing forecasting errors into the system. Lee (1993, 1996) and Zhao and Lam (1997) extended the studies by Sridharan et al (1987Sridharan et al ( , 1988) from single-level systems to multi-level MRP systems and discovered that some findings in single-level systems cannot be generalized to multi-level systems.…”

“…The other is to use a forecasting model to make forecasts based on previous demand. The first approach was used by Lee and Adam (1986), Sridharan and Berry (1990a), LaForge (1990 and, etc. while the second approach was used by Zhao and Lee (1993), Zhao et al (1995), etc.…”