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Article . 2018
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Production planning with multiple production lines: Forward algorithm and insights on process design for volume flexibility

Production planning with multiple production lines: forward algorithm and insights on process design for volume flexibility
Authors: Suresh Chand; Sunantha Teyarachakul Prime; Suresh Sethi;

Production planning with multiple production lines: Forward algorithm and insights on process design for volume flexibility

Abstract

AbstractThis paper considers the production planning problem of a firm that produces a single product using a process that has multiple production lines (or machines) in parallel, each with a finite production capacity. Specifically, the firm has m parallel production lines, each with capacity of P units per period. If needed, the firm can adjust the production rate in a period by adjusting the number of lines it operates in the period. The firm faces time‐varying demands. The objective is to find a production plan that meets the demands over the problem horizon and minimizes the sum of setup, holding and variable production costs. The paper develops an efficient forward dynamic programming algorithm and uses it to develop managerial insights on the effect of process design on “volume flexibility,” which is defined as “the ability to be operated profitably at different output levels.” Some forecast horizon results are also developed. The firm can use the results in the paper to optimize the process design for the demand it faces.

Keywords

forecast horizons, process design, Deterministic scheduling theory in operations research, production planning, increasing variable cost, Dynamic programming, volume flexibility, Production models, finite production rate

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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