Effects of forecast errors on optimal utilisation in aggregate production planning with stochastic customer demand

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

The hierarchical structure of production planning has the advantage of assigning different decision variables to their respective time horizons and therefore ensures their manageability. However, the restrictive structure of this top-down approach implying that upper level decisions are the constraints for lower level decisions also has its shortcomings. One problem that occurs is that deterministic mixed integer decision problems are often used for long-term planning, but the real production system faces a set of stochastic influences. Therefore, a planned utilisation factor has to be included into this deterministic aggregate planning problem. In practice, this decision is often based on past data and not consciously taken. In this paper, the effect of long-term forecast error on the optimal planned utilisation factor is evaluated for a production system facing stochastic demand and the benefit of exploiting this decisions potential is discussed. Overall costs including capacity, backorder and inventory costs, are determined with simulation for different multi-stage and multi-item production system structures. The results show that the planned utilisation factor used in the aggregate planning problem has a high influence on optimal costs. Additionally, the negative effect of forecast errors is evaluated and discussed in detail for different production system environments.

Original languageEnglish
Pages (from-to)3718-3735
Number of pages18
JournalInternational Journal of Production Research
Volume54
Issue number12
DOIs
Publication statusPublished - 17 Jun 2016

Keywords

  • aggregate production planning
  • demand and forecast uncertainty
  • MRP II
  • production planning
  • simulation

Fingerprint Dive into the research topics of 'Effects of forecast errors on optimal utilisation in aggregate production planning with stochastic customer demand'. Together they form a unique fingerprint.

Cite this