A sequential lot sizing heuristic with optimal average performance
Management Science
Eyeballing heuristics for dynamic lot size problems
Computers and Operations Research
Questioning the relative virtues of dynamic lot sizing rules
Computers and Operations Research
Ending Inventory Valuation in Multiperiod Production Scheduling
Management Science
Improved Rolling Schedules for the Dynamic Single-Level Lot-Sizing Problem
Management Science
A holding cost bound for the economic lot-sizing problem with time-invariant cost parameters
Operations Research Letters
A comparison of methods for lot-sizing in a rolling horizon environment
Operations Research Letters
On the power of lookahead in online lot-sizing
Operations Research Letters
A holding cost bound for the economic lot-sizing problem with time-invariant cost parameters
Operations Research Letters
Online lot-sizing problems with ordering, holding and shortage costs
Operations Research Letters
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In this paper, we analyze the worst-case performance of heuristics for the classical economic lot-sizing problem with time-invariant cost parameters. We consider a general class of online heuristics that is often applied in a rolling-horizon environment. We develop a procedure to systematically construct worst-case instances for a fixed time horizon and use it to derive worst-case problem instances for an infinite time horizon. Our analysis shows that any online heuristic has a worst-case ratio of at least 2.