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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Approximate trade-off between minimisation of total weighted tardiness and minimisation of carbon dioxide (CO_2) emissions in bi-criteria batch scheduling problem
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Approximate trade-off between minimisation of total weighted tardiness and minimisation of carbon dioxide (CO_2) emissions in bi-criteria batch scheduling problem

机译：在双标准批处理调度问题中，在最小化总加权拖延性和最小化二氧化碳（CO_2）排放量之间进行近似权衡

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摘要

The quantity of carbon dioxide (CO_2) emissions is one of the most widely recognised measures of environmental sustainability. Given the mounting concern about climate change and global warming, managers are facing growing pressure to reduce CO_2 emissions. In practice, other than CO_2 emissions, managers may be concerned with other objectives when making a scheduling decision. This work develops the ε-archived genetic algorithm (ε-AGA) to examine two batch scheduling problems with the goal of minimising CO_2 emissions and the traditional due date-based objective of minimising total weighted tardiness (TWT). Experimental results show that in terms of both quality and diversity of solutions, ε-AGA outperforms NSGA-II for same computation time limit as the stopping criteria. Several interesting observations are made. (1) These two objectives conflict with each other; (2) jobs that arrive soon after each other reduce makespan, and so reduce CO_2 emissions; (3) given a set of m identical batching machines, the due dates of jobs do not seem to substantially influence CO_2 emissions; and (4) in purchasing a machine, the variation in power consumption among machines is critical to reducing the TWT.
机译：二氧化碳（CO_2）排放量是环境可持续性最广泛认可的措施之一。鉴于越来越多的人关注气候变化和全球变暖，管理人员正面临越来越大的减少CO_2排放的压力。在实践中，除了CO_2排放外，管理者在制定计划决策时可能还会关注其他目标。这项工作开发了ε存档遗传算法（ε-AGA），以检查两个批处理调度问题，以最小化CO_2排放为目标，并基于传统的基于到期日的目标，以最小化总加权拖延（TWT）。实验结果表明，就解决方案的质量和多样性而言，在相同的计算时限内，ε-AGA的性能优于NSGA-II。进行了一些有趣的观察。 （1）这两个目标相互冲突; （2）紧接而来的工作减少了有效期，从而减少了CO_2的排放; （3）给定一套m台相同的配料机，工作的到期日期似乎并没有实质性地影响CO_2的排放; （4）在购买机器时，机器间功耗的变化对于降低总吨位至关重要。

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