Scheduling on a single machine under time-of-use electricity tariffs

Fang, Kan; Uhan, Nelson A.; Zhao, Fu; Sutherland, John W.

doi:10.1007/s10479-015-2003-5

Cited by 109 publications

(51 citation statements)

References 23 publications

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“…To specifically reduce the energy cost under ToUP, a greedy insertion heuristic was proposed in (Che et al, 2016) for a single machine scheduling model, such that it yielded high-quality solutions within 10 sec even for the instance with 5000 jobs. Fang et al (2016) further investigated the same scheduling problem under the cases of uniform and scalable machine speeds.…”

Section: Energy-efficient Production Schedulingmentioning

confidence: 99%

Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: An empirical study

Gong

Wee

Pessemier

et al. 2017

Journal of Cleaner Production

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With the penetration of smart grid into factories, energyefficient production scheduling has been emerged. It shifts flexible production loads to lower-priced periods to reduce energy cost for the same production task. However, the existing methods only focus on integrating energy awareness to conventional production scheduling models. They ignore the labor cost which is shift-based and follows an opposite trend of energy cost. For instance, the energy cost is lower during nights while the labor cost is higher. Therefore, this paper proposes a method for energy-efficient and labor-aware production scheduling at the unit process level. This integrated scheduling model is mathematically formulated. Besides the state-based energy model and genetic algorithm-based optimization, a continuous-time shift accumulation heuristic is proposed to synchronize power states and labor shifts. In a case study of a Belgian plastic bottle manufacturer, a set of empirical sensitivity analyses were performed to investigate the impact of energy and labor awareness, as well as the production-related factors that influence the economic performance of a schedule. Furthermore, the demonstration was performed in 9 large-scale test instances, which encompass the cases where energy cost is minor, medium, and major compared to the joint energy and labor cost. The results have proven that the ignorance of labor in existing energy-efficient production scheduling studies increases the joint energy and labor cost, although the energy cost can be minimized. To achieve effective production cost reduction, energy and labor awareness are recommended to be jointly considered in production scheduling. 1Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: an empirical study AbstractWith the penetration of smart grid into factories, energy-efficient production scheduling has been emerged. It shifts flexible production loads to lower-priced periods to reduce energy cost for the same production task. However, the existing methods only focus on integrating energy awareness to conventional production scheduling models. They ignore the labor cost which is shift-based and follows an opposite trend of energy cost. For instance, the energy cost is lower during nights while the labor cost is higher. Therefore, this paper proposes a method for energy-efficient and laboraware production scheduling at the unit process level. This integrated scheduling model is mathematically formulated. Besides the state-based energy model and genetic algorithm-based optimization, a continuous-time shift accumulation heuristic is proposed to synchronize power states and labor shifts. In a case study of a Belgian plastic bottle manufacturer, a set of empirical sensitivity analyses were performed to investigate the impact of energy and labor awareness, as well as the production-related factors that influence the economic performance of a schedule. Furthermore, the demonstration was performed in 9 large-scale test instan...

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Section: Energy-efficient Production Schedulingmentioning

confidence: 99%

Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: An empirical study

Gong

Wee

Pessemier

et al. 2017

Journal of Cleaner Production

View full text Add to dashboard Cite

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“…Yao et al, 1995;Pruhs et al, 2008;Kwon and Kim, 2005;Angel et al, 2012) or in manufacturing systems (e.g. Fang et al, 2011Fang et al, , 2014Dai et al, 2013;Fang and Lin, 2013;Liu and Huang, 2014), while others have examined scheduling problems with powerdown mechanism of machines (e.g. Mouzon and Yildirim, 2008;Dai et al, 2013;Pach et al, 2014).…”

Section: Literature Reviewmentioning

confidence: 99%

An efficient greedy insertion heuristic for energy-conscious single machine scheduling problem under time-of-use electricity tariffs

Che

Zeng

Lyu

2016

Journal of Cleaner Production

118

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“…Note that the Problem U-pyr is the same as our problem. Based on Fang et al [29], Che et al [9] investigated a continuous-time MILP model for Problem U-pyr and developed a greedy insertion heuristic algorithm(GIH) that is the most classic method for this problem until now, according to our best knowledge. In their algorithm, the jobs are inserted into available periods with lower electricity prices in sequence, and the jobs with higher power consumption rates are mostly assigned to periods with lower electricity prices by traversing all non-full "forward blocks" and "backward blocks".…”

Section: Introductionmentioning

confidence: 99%

“…However, Fang et al [29] did not establish a complete mathematical model for the single machine scheduling problem (Problem U-pyr) under TOU electricity tariffs, and their algorithm is only feasible in the condition that all the jobs have the same workload and the TOU tariffs follow a so-called pyramidal structure. Regrettably, the TOU electricity tariffs rarely follow a complete pyramidal structure in most provinces in China.…”

Section: Introductionmentioning

confidence: 99%

“…Regrettably, the TOU electricity tariffs rarely follow a complete pyramidal structure in most provinces in China. To perfect the theory of Fang et al [29], Che et al [9] developed a new model and algorithm, but their algorithm requires that all the jobs must traverse all non-full "forward blocks" and "backward blocks", causing a strong high-time complexity. Especially when the processing times of the jobs are relatively short, it usually takes several jobs to fill one period and generates uneven remaining idle times, which leads to an increase in the number of forward and backward blocks required to be calculated.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A New Greedy Insertion Heuristic Algorithm with a Multi-Stage Filtering Mechanism for Energy-Efficient Single Machine Scheduling Problems

et al. 2018

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To improve energy efficiency and maintain the stability of the power grid, time-of-use (TOU) electricity tariffs have been widely used around the world, which bring both opportunities and challenges to the energy-efficient scheduling problems. Single machine scheduling problems under TOU electricity tariffs are of great significance both in theory and practice. Although methods based on discrete-time or continuous-time models have been put forward for addressing this problem, they are deficient in solution quality or time complexity, especially when dealing with large-size instances. To address large-scale problems more efficiently, a new greedy insertion heuristic algorithm with a multi-stage filtering mechanism including coarse granularity and fine granularity filtering is developed in this paper. Based on the concentration and diffusion strategy, the algorithm can quickly filter out many impossible positions in the coarse granularity filtering stage, and then, each job can find its optimal position in a relatively large space in the fine granularity filtering stage. To show the effectiveness and computational process of the proposed algorithm, a real case study is provided. Furthermore, two sets of contrast experiments are conducted, aiming to demonstrate the good application of the algorithm. The experiments indicate that the small-size instances can be solved within 0.02 s using our algorithm, and the accuracy is further improved. For the large-size instances, the computation speed of our algorithm is improved greatly compared with the classic greedy insertion heuristic algorithm.

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Scheduling on a single machine under time-of-use electricity tariffs

Cited by 109 publications

References 23 publications

Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: An empirical study

Integrating labor awareness to energy-efficient production scheduling under real-time electricity pricing: An empirical study

An efficient greedy insertion heuristic for energy-conscious single machine scheduling problem under time-of-use electricity tariffs

A New Greedy Insertion Heuristic Algorithm with a Multi-Stage Filtering Mechanism for Energy-Efficient Single Machine Scheduling Problems

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