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Green Production Scheduling/Planning with Parallel-Machine Layout for Multiple Orders and Diversified Due Dates

Authors: ChunHsiung Lan -; HaiMing Chen -; MeiHsiu Chen -; ChihWei Chiu -; ChengJui Tsai -;

Green Production Scheduling/Planning with Parallel-Machine Layout for Multiple Orders and Diversified Due Dates

Abstract

This paper proposes an Integer Nonlinear Programming (INLP) mathematical model to investigate the practical situations of production scheduling and planning with a parallel-machine layout focusing on multiple orders, diversified delivery deadlines, and multiple types of products. Production cost, machine setup cost, product holding cost, shortage cost, and antipollution cost are also considered in this model to achieve the goal of total cost optimization. This study creates a highly repeated characteristic because the proposed mathematical model and its solving procedure, (Accumulation and Backtrack staged Scheduling Approach, ABSSA) method, are constructed by the packaged software. Therefore, this study has its value for practical applications, and it is suitable for diversified production scheduling as well as the real-time scheduling of production planning. For production scheduling and planning of parallel machines, this study has provided a valuable decision support tool.

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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!
0
Average
Average
Average
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