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AN ENERGY-EFFICIENT BI-OBJECTIVE NO-WAIT PERMUTATION FLOWSHOP SCHEDULING PROBLEM TO MINIMIZE TOTAL TARDINESS AND TOTAL ENERGY CONSUMPTION
Computers & Industrial Engineering ( IF 7.9 ) Pub Date : 2020-07-01 , DOI: 10.1016/j.cie.2020.106431
Damla Yüksel , M. Fatih Taşgetiren , Levent Kandiller , Liang Gao

Abstract In manufacturing scheduling, sustainability concerns that raise from the service-oriented performance criteria have seldom been studied in the literature. This study aims to fill this gap in the literature by integrating the different energy consumption levels at the operational level. Since energy-efficient scheduling ideas have recently been increasing its popularity in industry due to the need for sustainable production, this study will be a good resource for future energy-efficient scheduling problems. Energy consumption in high volume manufacturing is a significant cost item in most industries. Potential energy saving mechanisms are needed to be integrated into manufacturing facilities for cost minimization at the operational level. A leading energy-saving mechanism in manufacturing is to be able to adapt/change the machine speed levels which exactly determines the energy consumption of the machines. Hence, in this study, the afore-mentioned framework is applied to the no-wait permutation flowshop scheduling problem (NWPFSP) which is a variant of classical permutation flowshop scheduling problems. However, it has various critical applications in industries such as chemical, pharmaceutical, food-processing, etc. This study proposes both mixed-integer linear programming (MILP) and constraint programming (CP) model formulations for the energy-efficient bi-objective no-wait permutation flowshop scheduling problems (NWPFSPs) considering the total tardiness and the total energy consumption minimization simultaneously. This problem treats total energy consumption as a second objective. Thus, the trade-off between the total tardiness – a service level measurement indicator – and the total energy consumption – a sustainability level indicator – is analyzed in this study. Furthermore, due to the NP-hardness nature of the first objective of the problem, a novel multi-objective discrete artificial bee colony algorithm (MO-DABC), a traditional multi-objective genetic algorithm (MO-GA) and a variant of multi-objective genetic algorithm with a local search (MO-GALS) are proposed for the bi-objective no-wait permutation flowshop scheduling problem. Besides the proposed algorithms are compared with the multi-objective energy-efficient algorithms from the literature. Consequently, a comprehensive comparative metaheuristic analysis is carried out. The computational results indicate that the proposed MO-DABC algorithm outperforms MILP, CP, MO-GA, MO-GALS, and algorithms from the literature in terms of both cardinality and quality of the solutions. The powerful results of this study show that the proposed models and algorithms can be adapted to other energy-efficient scheduling problems such as no-idle flowshop, blocking flowshop and job-shop scheduling problems or to other higher-level integrated manufacturing problems.

中文翻译:

一个节能的双目标无等待置换流程调度问题,以最大限度地减少总延误和总能源消耗

摘要 在制造调度中,文献中很少研究由面向服务的性能标准引起的可持续性问题。本研究旨在通过整合运营层面的不同能源消耗水平来填补文献中的这一空白。由于可持续生产的需要,节能调度思想最近在工业中越来越受欢迎,因此这项研究将成为解决未来节能调度问题的良好资源。大批量制造中的能源消耗是大多数行业的重要成本项目。需要将潜在的节能机制整合到制造设施中,以最大限度地降低运营成本。制造业领先的节能机制是能够适应/改变机器速度水平,这正是机器能耗的决定因素。因此,在本研究中,上述框架应用于无等待置换流水车间调度问题(NWPFSP),这是经典置换流水车间调度问题的变体。然而,它在化工、制药、食品加工等行业有各种关键应用。 本研究提出了混合整数线性规划 (MILP) 和约束规划 (CP) 模型公式,用于节能双目标无- 同时考虑总延迟和总能耗最小化的等待置换流水车间调度问题(NWPFSPs)。该问题将总能耗视为第二个目标。因此,本研究分析了总延迟(服务水平测量指标)与总能源消耗(可持续性水平指标)之间的权衡。此外,由于问题的第一个目标的 NP 硬度性质,新的多目标离散人工蜂群算法 (MO-DABC)、传统的多目标遗传算法 (MO-GA) 和多目标的变体针对双目标无等待置换流水车间调度问题,提出了具有局部搜索的目标遗传算法(MO-GALS)。此外,将所提出的算法与文献中的多目标节能算法进行了比较。因此,进行了全面的比较元启发式分析。计算结果表明,所提出的 MO-DABC 算法在解决方案的基数和质量方面都优于 MILP、CP、MO-GA、MO-GALS 和文献中的算法。本研究的有力结果表明,所提出的模型和算法可以适用于其他节能调度问题,如无空闲流水车间、阻塞流水车间和作业车间调度问题,或其他更高级别的集成制造问题。
更新日期:2020-07-01
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