HEURISTIC LOT‐SIZING PERFORMANCE IN A ROLLING‐SCHEDULE ENVIRONMENT*
研究了滚动计划实施对三种经典批量决策方法（部分周期成本平衡、Silver-Meal和Wagner-Whitin算法）及改进版Silver-Meal方法绩效的影响，发现特定条件下Silver-Meal启发式方法成本表现优于Wagner-Whitin算法。
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.