A Job-shop with an Energy Threshold Issue Considering Operations with Consumption Peaks

Kemmoe, Sylverin; Lamy, Damien; Tchernev, Nikolay

doi:10.1016/j.ifacol.2015.06.179

Cited by 11 publications

(10 citation statements)

References 18 publications

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“…One important reason for this prevalent usage of metaheuristics is that production scheduling on the shop floor intrinsically requires fast yet high-quality decision making [22]. This also explains why optimization by a standard solver [20,24] or a heuristic [29] is not extensively used, of which the computation time and tractability are very sensitive to additional constraints and an increasing problem size.…”

Section: Literature Review On Energy-aware (Flexible) Job Shop Schedumentioning

confidence: 99%

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Energy- and labor-aware flexible job shop scheduling under dynamic electricity pricing: A many-objective optimization investigation

Gong

Pessemier

Martens

et al. 2019

Journal of Cleaner Production

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Energy-aware production scheduling is a promising way to adapt the factories' energy consumption behavior to the volatile electricity prices in the demand response initiative of smart grids. However, it may not be economical by simply scheduling production loads to the periods with lower electricity prices, as these periods often have higher labor wage, e.g., nights and weekends. Based on this gap, this paper proposes a many-objective integrated energy-and labor-aware flexible job shop scheduling model. Many objectives refer to the number of optimization objectives surpasses three (i.e., five objectives: makespan, total energy cost, total labor cost, maximal workload, and total workload), whereas the existing energy-aware production scheduling research is limited within three objectives. To enable energy awareness in the conventional production scheduling algorithms, a state-based shop floor wide energy model is proposed. To enable labor awareness, the number and type of human workers are matched to the scheduled production loads, with varying labor wage over shifts. As one of the most complex shop floor configurations, the partial flexible job shop further considers job recirculation and operation sequence-dependent machine setup times. The recently-proposed nondominated sorting genetic algorithm-III (NSGA-III) is tailored for this many-objective optimization problem (MaOP), including scheduling solution encoding and decoding, crossover, mutation, and solution evaluation using the energy-and labor-aware discrete-event simulation framework. Through numerical experiments under real-time pricing (RTP) and time-of-use pricing (ToUP), insights are statistically obtained on the relation among these five production objectives; the effectiveness and efficiency of NSGA-III in solving a MaOP are also demonstrated. This proposed scheduling method can be used to automated and enhance the decision making of factory managers in jointly allocating machine, human worker, and energy resources on the shop floor, such that the production cost is minimized even under time-varying electricity and labor prices.

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Section: Literature Review On Energy-aware (Flexible) Job Shop Schedumentioning

confidence: 99%

“…The labor wage in a day also varies, which increases in the night shift than in the other shifts on the same day. 24 SH sh δ = (16) Within one shift (sh), once a personnel type (pt) is required by an involved power state (s), this pt will be included in this sh ( 1).…”

Section: Total Labor Costmentioning

confidence: 99%

Energy- and labor-aware flexible job shop scheduling under dynamic electricity pricing: A many-objective optimization investigation

Gong

Pessemier

Martens

et al. 2019

Journal of Cleaner Production

View full text Add to dashboard Cite

show abstract

“…In a previous work [1], a linear model for the Job-shop with Energy Consumption Threshold (JS-ECT) is proposed where each operation has two different energy consumption: a high energy consumption at the beginning of the operation, called a peak consumption, and a lower energy consumption for the rest of the operation. In this mathematical formulation, the energy threshold is constant during the schedule.…”

Section: Related Workmentioning

confidence: 99%

“…A linear model is proposed in this paper which goal is to extend a previous work [1] concerning the scheduling in a job-shop like manufacturing environment with an energy threshold which must not be exceeded. Operations presenting two distinct energy consumptions are considered as follows: a peak consumption at the beginning of the process and a nominal consumption after the peak's end.…”

Section: Introductionmentioning

confidence: 99%

“…Operations presenting two distinct energy consumptions are considered as follows: a peak consumption at the beginning of the process and a nominal consumption after the peak's end. The previously proposed linear model [1] is extended in order to manage variations in the allowed energy threshold. Thus, the objective is to find the best feasible schedule of the problem where operations need electricity in order to be realized and where the instantly usable energy is constrained and varies with time.…”

Section: Introductionmentioning

confidence: 99%

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Job-Shop like Manufacturing System with Time Dependent Energy Threshold and Operations with Peak Consumption

Kemmoé-Tchomté

Lamy

Tchernev

2015

IFIP Advances in Information and Communication Technology

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A memetic NSGA-II for the multi-objective flexible job shop scheduling problem with real-time energy tariffs

Burmeister,

Guericke,

Schryen

2023

Flex Serv Manuf J

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Rising costs for energy are increasingly becoming a vital factor for the production planning of manufacturing companies. Manufacturers face the challenge to react to dynamic energy prices and design energy cost efficient schedules in their production planning. In the literature, the energy cost-aware Flexible Job Shop Scheduling Problem addresses minimization of both makespan and energy costs. Recent studies provide multi-objective approaches to model the trade-off of minimizing makespan and energy costs. However, the literature is limited to coarse-grained time periods and does not consider dynamic tariffs where costs change at short intervals, so that production schedules may fall short on energy costs. We aim to close this research gap by considering frequently changing real-time energy tariffs. We propose a multi-objective memetic algorithm based on the non-dominated sorting genetic algorithm (NSGA-II) with both makespan and energy cost minimization as the objectives. We evaluate our approach by conducting computational experiments using prominent FJSP-benchmark instances from the literature, which we supplement with empiric dynamic energy prices. We show results on method performance and compare the memetic NSGA-II with the results of an exact state-of-the-art solver. To investigate the trade-off between a short makespan and low energy costs, we present solutions on the approximated Pareto front and discuss our results.

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A Job-shop with an Energy Threshold Issue Considering Operations with Consumption Peaks

Cited by 11 publications

References 18 publications

Energy- and labor-aware flexible job shop scheduling under dynamic electricity pricing: A many-objective optimization investigation

Energy- and labor-aware flexible job shop scheduling under dynamic electricity pricing: A many-objective optimization investigation

Job-Shop like Manufacturing System with Time Dependent Energy Threshold and Operations with Peak Consumption

A memetic NSGA-II for the multi-objective flexible job shop scheduling problem with real-time energy tariffs

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