This paper presents two new lot-sizing heuristics which are simple but naive in the sense that cost data are ignored in determining lot-sizes. These new rules, together with two other well-known non-cost-based heuristics: the Lot-for-Lot and Fixed Period Requirement rules, are tested and compared with the Wagner-Whitin (WW) optimization algorithm. Under various testing conditions, the performances of these heuristics, despite their naivete, are found to be comparable to that of the WW algorithm. The implication of these results is that non-cost-based heuristics should deserve more considerable from both researchers and practitioners because of their simplicity, computational efficiency and effectiveness for lot-sizing decisions.
ASJC Scopus subject areas
- Computer Science(all)