HEURISTIC LOT‐SIZING PERFORMANCE IN A ROLLING‐SCHEDULE ENVIRONMENT*

Joseph D. Blackburn · ROBERT A. MILLEN

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Supply Chain and Inventory Management Management and Optimization Techniques Scheduling and Optimization Algorithms

Abstract

Abstract This paper examines the impact of a rolling‐schedule implementation on the performance of three of the better known lot‐sizing methods for single‐level assembly systems——Part‐Period‐Cost‐Balancing, Silver‐Meal, and Wagner‐Whitin algorithms—and a modified version of the Silver‐Meal procedure. The main finding is that under certain conditions the computationally simpler Silver‐Meal heuristic can provide cost performance superior to that of the Wagner‐Whitin algorithm.

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References

1958Dynamic Version of the Economic Lot Size Model 2004Dynamic Version of the Economic Lot Size Model 1975Planning Horizons for the Dynamic Lot Size Model: Zabel vs. Protective Procedures and Computational Results

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1991A theory of rolling horizon decision making 1989Purchasing Policy of New Containers Considering the Random Returns of Previously Issued Containers 2013Rolling horizon planning in supply chains: review, implications and directions for future research 1986Forecasting Error Evaluation in Material Requirements Planning (MRP) Production-Inventory Systems 1984Lot-sizing under uncertainty in a rolling schedule environment 2000Improved Rolling Schedules for the Dynamic Single-Level Lot-Sizing Problem 2011A new Silver–Meal based heuristic for the single-item dynamic lot sizing problem with returns and remanufacturing 1983COST INCREASES DUE TO DEMAND UNCERTAINTY IN MRP LOT SIZING

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